208 Big Data Architect Jobs in Faridabad

Hello Folks, Hiring Currently !! Job Title: GCP Data Engineer Contact: Pooja Patil (poojapatil@acme-services.in) Job Details: - Skills: - BigQuery - GCP Big Data - Airflow - PySpark/Spark- Experience: 5+ years- Locations: Bangalore, Pune, Mumbai, Gurgaon  If you're interested and match the requirements, you can share your resume with the mentioned email address.

Location - LTIM Pan IndiaExperience - 5+to 12+ yrsGeneric JD-Mandatory Skills - Data Science, Gen AI, Python, RAG and Azure/AWS/GCP, AI/ML, NLP Secondary - (Any) Machine Learning, Deep Learning, ChatGPT, Langchain, Prompt, vector stores, RAG, llama, Computer vision, Deep learning, Machine learning, OCR, Transformer, regression, forecasting, classification, hyper parameter tunning, MLOps, Inference, Model training, Model DeploymentJD_ More than 6 years of experience in Data Engineering, Data Science and AI / ML domainExcellent understanding of machine learning techniques and algorithms, such as GPTs, CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests, etc.Experience using business intelligence tools (e.g. Tableau, PowerBI) and data frameworks (e.g. Hadoop)Experience in Cloud native skills.Knowledge of SQL and Python; familiarity with Scala, Java or C++ is an assetAnalytical mind and business acumen and Strong math skills (e.g. statistics, algebra)Experience with common data science toolkits, such as TensorFlow, KERAs, PyTorch, PANDAs, Microsoft CNTK, NumPy etc. Deep expertise in at least one of these is highly desirable.Experience with NLP, NLG and Large Language Models like BERT, LLaMa, LaMDA, GPT, BLOOM, PaLM, DALL-E, etc.Great communication and presentation skills. Should have experience in working in a fast-paced team culture.Experience with AIML and Big Data technologies like AWS SageMaker, Azure Cognitive Services, Google Colab, Jupyter Notebook, Hadoop, PySpark, HIVE, AWS EMR etc.Experience with NoSQL databases, such as MongoDB, Cassandra, HBase, Vector databasesGood understanding of applied statistics skills, such as distributions, statistical testing, regression, etc.Should be a data-oriented person with analytical mind and business acumen.

Job Description  We are seeking a seasoned GCP Data Analytics professional with extensive experience in Big Data technologies and Google Cloud Platform services to design and implement scalable data solutionsDesign develop and optimize data pipelines using GCP BigQuery Dataflow and Apache Airflow to support largescale data analytics Utilize the Big Data Hadoop ecosystem to manage and process vast datasets efficiently Collaborate with crossfunctional teams to gather requirements and deliver reliable data solutions Ensure data quality consistency and integrity across multiple data sources Monitor and troubleshoot data workflows to maintain high system availability and performance Stay updated with emerging trends and best practices in GCP data analytics and big data technologiesRoles and Responsibilities  Implement and manage ETL processes leveraging GCP services such as BigQuery Dataflow and Airflow Develop.  Scalable maintainable and reusable data pipelines to support business intelligence and analytics needs.  Optimize SQL queries and data models for performance and cost efficiency in BigQuery.  Integrate Hadoop ecosystem components with GCP services to enhance data processing capabilities  Automate workflow orchestration using Apache Airflow for seamless data operations  Collaborate with data engineers analysts and stakeholders to ensure alignment of data solutions with organizational goals  Participate in code reviews testing and deployment activities adhering to best practices   Mentor junior team members and contribute to continuous improvement initiatives within the data engineering team Mandatory Skills :    GCP Storage,GCP BigQuery,GCP DataProc,GCP Cloud Composer,GCP DMS,Apache airflow,Java,Python,Scala,GCP Datastream,Google Analytics Hub,GCP Workflows,GCP Dataform,GCP Datafusion,GCP Pub/Sub,ANSI-SQL,GCP Dataflow,GCP Data Flow,GCP Cloud Pub/Sub,Big Data Hadoop Ecosystem

As a skilled Data Developer, you will be responsible for designing, building, and maintaining efficient and scalable ETL/ELT data pipelines. Your expertise in Python or PySpark, data integration, and modern big data platforms will be essential in ensuring reliable and high-quality data delivery across systems. You will collaborate closely with data engineers, analysts, and stakeholders to meet the organization's data needs. Key Responsibilities: - Design, develop, and maintain efficient and scalable ETL/ELT data pipelines using Python or PySpark. - Collaborate with data engineers, analysts, and business stakeholders to understand requirements and deliver technical data solutions. - Perform data cleansing, transformation, and validation to ensure data accuracy, consistency, and integrity. - Optimize and troubleshoot performance issues in data processing jobs and workflows. - Implement data integration solutions for various sources, including databases, APIs, and file systems. - Participate in code reviews, testing, and deployment to maintain high coding standards. - Maintain comprehensive documentation for data workflows, systems, and best practices. Qualifications Required: - Hands-on experience with Python or PySpark. - Knowledge of data integration techniques and best practices. - Familiarity with modern big data platforms. - Strong problem-solving and analytical skills. - Excellent communication and collaboration abilities. Please note that the company, Credent, is a consulting provider specializing in technology-driven solutions aimed at streamlining technology and business processes in SMEs and large enterprises.,

Role Overview: On Team Xbox, you will be part of the Xbox Platform Data Intelligence Team, aiming to empower the world's 3 billion gamers by shaping the next generation of data and analytics capabilities for Xbox. Your role will involve working closely with engineering and product management to design, implement, and evolve innovative capabilities that will drive analytics and insights on engineering features. You will play a crucial part in influencing data-driven decision-making across Xbox Leadership, Finance, Business Planning, and Engineering teams. Key Responsibilities: - Work within and across teams to solve complex technical challenges. - Develop engineering best practices by continuously evaluating processes and reporting to identify opportunities for improvement, enhancement, and automation with a fundamental understanding of the end-to-end scenario. - Utilize judgement and rating schemes to turn qualitative information into quantitative estimates. - Proficiency in scenario analytics and mining for insights. - Measure the success and usage patterns of the product/feature at various levels as well as key engineering metrics. - Contribute to a data-driven culture as well as a culture of experimentation across the organization. - Create dashboards in Power BI and Azure Data Explorer. Qualifications: Required: - Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years of experience in business analytics, data science, software development, data modeling, or data engineering work OR Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) of experience in business analytics, data science, software development, or data engineering work OR equivalent experience. - Experience working with cloud-based technologies, including relational databases, data warehouse, big data (e.g., Hadoop, Spark), orchestration/data pipeline tools, data lakes. - Self-motivated and organized to deliver results. Preferred: - Experience with Azure Analytics stack, e.g., Azure Data Lake, Azure Data Factory, Azure Synapse, Azure Data Explorer (Kusto), Azure Cosmos DB, Azure logic apps, Fabric/Power BI. - Experience in modern DevOps practices (including Git, CI/CD). - Good interpersonal and communication (verbal and written) skills, including the ability to effectively communicate with both business and technical teams. - Ability to use judgement and rating schemes to turn qualitative information into quantitative estimates. - Proficiency in scenario analytics and mining for insights.,

You will be responsible for supporting data and analytics solutions across projects as an Azure Data Engineer with 3 to 8 years of experience. Collaborating with various projects, you will create data solutions for a variety of business use cases. Your role will involve driving innovation within Data Engineering to shape the future of data and analytics technology. As a critical team member, you will design and develop highly complex data projects, identifying gaps in the data stack and guiding advancements for the team. You will provide technical expertise in all project phases, including analysis, design, development, and implementation of cutting-edge solutions. Your input will continuously shape and improve the data environment beyond the team boundaries. Key Responsibilities: - Collaborate with various projects to create data solutions for different business use cases - Drive innovation within Data Engineering to influence the future of data and analytics technology - Design and develop highly complex data projects - Identify gaps and weaknesses in the data stack, guiding advancements for the team - Provide technical expertise in all project phases, including analysis, design, development, and implementation - Shape and improve the data environment beyond team boundaries - Understand UI needs, backend design, and data design to create backend code - Run diagnostic tests, repair defects, and provide technical support - Document Node.js processes and prepare reports - Design and implement APIs, integrating with third-party APIs as needed - Develop and maintain databases using technologies such as MongoDB or MySQL - Create reusable code and libraries for future use - Optimize applications for maximum speed and scalability - Troubleshoot and debug issues, providing timely resolutions Qualifications Required: - Excellent knowledge and experience in Azure Data Services (like ADF, etc.) along with Databricks - Good knowledge and expertise in SQL, Python, PySpark - Good understanding of ETL & Data warehousing concepts - Excellent written & spoken communication skills for interactions with customers and stakeholders - Ability to understand requirements and architecture and translate them into implementation following best practices - Self-driven with an excellent learning attitude - Experience in Snowflake Datawarehouse Good to have: - Experience & conceptual knowledge of Bigdata technologies such as Hadoop, HDFS, Hive, Spark - Knowledge and exposure to Databricks - Experience with ETL tools like Matillion, DBT, etc. - Exposure to other cloud platforms,

As a Lead Data Analyst in the Data & Analytics team, you will play a crucial role in analyzing large and complex datasets to extract actionable insights. Your responsibilities will include designing and developing end-to-end BI solutions using Power BI, SQL, DAX, and Power Query. Additionally, you will be building scalable ETL pipelines and data workflows utilizing Azure Data Factory, Databricks, and Delta Lake. Your expertise will be essential in leading data modeling efforts to optimize reporting performance with Star and Snowflake schemas. Your role will also involve migrating and managing cloud data platforms, especially Snowflake and Azure-based environments. Automation of repetitive data processing tasks using Python and ensuring high data quality will be part of your routine tasks. Key Responsibilities: - Analyze large and complex datasets to extract actionable insights and support strategic decision-making. - Design and develop end-to-end BI solutions using Power BI, SQL, DAX, and Power Query. - Build scalable ETL pipelines and data workflows using Azure Data Factory, Databricks, and Delta Lake. - Lead data modeling efforts using Star and Snowflake schemas to optimize reporting performance. - Migrate and manage cloud data platforms, especially Snowflake and Azure-based environments. - Automate repetitive data processing tasks using Python and streamline reporting operations. - Collaborate with cross-functional teams to gather business requirements, resolve data issues, and ensure high data quality. - Mentor junior team members and ensure documentation and adherence to best practices in data engineering. - Work with stakeholders across US and Indian teams, maintaining strong communication and delivery alignment. Qualifications Required: - 6-8 years of experience in delivering robust business intelligence solutions, advanced data modeling, and cloud-based data engineering. - Proficiency in BI & Visualization tools such as Power BI, DAX, Power Query, and Streamlit. - Strong knowledge of Data Platforms including SQL, Snowflake, Azure Synapse, and Delta Lake. - Experience with ETL & Pipelines using Azure Data Factory, PySpark, and Databricks. - Skilled in Programming & Automation with Python, Pandas, VBA, and Git. - Familiarity with other tools like SSAS, Confluence, HTML/CSS, and basics of Machine Learning. Please note: The JD does not provide any additional details of the company. As a Lead Data Analyst in the Data & Analytics team, you will play a crucial role in analyzing large and complex datasets to extract actionable insights. Your responsibilities will include designing and developing end-to-end BI solutions using Power BI, SQL, DAX, and Power Query. Additionally, you will be building scalable ETL pipelines and data workflows utilizing Azure Data Factory, Databricks, and Delta Lake. Your expertise will be essential in leading data modeling efforts to optimize reporting performance with Star and Snowflake schemas. Your role will also involve migrating and managing cloud data platforms, especially Snowflake and Azure-based environments. Automation of repetitive data processing tasks using Python and ensuring high data quality will be part of your routine tasks. Key Responsibilities: - Analyze large and complex datasets to extract actionable insights and support strategic decision-making. - Design and develop end-to-end BI solutions using Power BI, SQL, DAX, and Power Query. - Build scalable ETL pipelines and data workflows using Azure Data Factory, Databricks, and Delta Lake. - Lead data modeling efforts using Star and Snowflake schemas to optimize reporting performance. - Migrate and manage cloud data platforms, especially Snowflake and Azure-based environments. - Automate repetitive data processing tasks using Python and streamline reporting operations. - Collaborate with cross-functional teams to gather business requirements, resolve data issues, and ensure high data quality. - Mentor junior team members and ensure documentation and adherence to best practices in data engineering. - Work with stakeholders across US and Indian teams, maintaining strong communication and delivery alignment. Qualifications Required: - 6-8 years of experience in delivering robust business intelligence solutions, advanced data modeling, and cloud-based data engineering. - Proficiency in BI & Visualization tools such as Power BI, DAX, Power Query, and Streamlit. - Strong knowledge of Data Platforms including SQL, Snowflake, Azure Synapse, and Delta Lake. - Experience with ETL & Pipelines using Azure Data Factory, PySpark, and Databricks. - Skilled in Programming & Automation with Python, Pandas, VBA, and Git. - Familiarity with other tools like SSAS, Confluence, HTML/CSS, and basics of Machine Learning. Please note: The JD does not provide any additional details of the company.

As an experienced professional looking to advance your career in the IT industry, you have the opportunity to join Iris Software, one of India's Top 25 Best Workplaces. At Iris Software, you will be a part of a fast-growing IT services company that values talent, career aspirations, and fosters an award-winning work culture. Role Overview: - You will be responsible for developing complex, mission-critical applications using the latest technologies such as Spark, Scala, Hive, and Java. - Your role will involve working on high-value complex Application & Product Engineering, Data & Analytics, Cloud, DevOps, Data & MLOps, Quality Engineering, and Business Automation projects. Key Responsibilities: - Must have a minimum of 7 years of development experience - Experience as a big data developer with exposure to Java - Proficiency in Spark, Scala, Hive, and a strong background in SQL - Familiarity or experience with Cloud technologies is a plus Qualifications Required: - Mandatory competencies in Big Data (Hive, Spark), Database Programming (SQL), Scala programming language, and effective communication skills Joining Iris Software comes with its perks and benefits, including comprehensive health insurance, competitive salaries, flexible work arrangements, and ongoing learning opportunities. Experience a work environment where your success and happiness as an employee are valued and supported. If you are looking to be valued, inspired, and perform at your best, Iris Software is the place for you to realize your full potential and thrive in your career.,

As a Senior Data Architect at our company, you will play a crucial role in designing, building, and optimizing our data infrastructure and analytics platforms. You will lead and provide architectural guidance to the "SQUAD | DIGITAL PULSE" team, ensuring scalability, reliability, and efficiency while enabling data-driven insights across the organization. **Key Responsibilities:** - Define and design the future state data architecture aligning with business objectives and data strategy. - Lead the design and build of new data models and pipelines for financial results and operational insights. - Develop and maintain processes, standards, policies, guidelines, and governance for the data ecosystem. - Evaluate data-related tools and technologies, recommending implementation patterns. - Design and manage data integration processes into a central data lake, ensuring quality and accessibility. - Build and maintain ETL pipelines for data processing and structuring. - Manage and optimize the cloud data warehouse for efficient storage and querying. - Implement data quality checks and governance policies for data integrity and compliance. - Prepare and model data for visualization platforms, enabling self-service analytics. - Collaborate with stakeholders to refine reporting, enhance data identity, and improve platform reliability. - Provide technical expertise and mentorship to Data Engineers and Data Analysts. - Review data models with technical and business audiences. **Qualifications Required:** - Bachelor's degree in Computer Science, Engineering, or a similar field. - Additional Certification in Data Management or cloud data platforms preferred. - 10-12+ years of IT experience with a focus on data warehouse/database projects. - Extensive experience with Cloud Big Data technologies in a multi-cloud environment. - Expertise in modern data platforms and cloud databases. - Proficiency in Data Warehousing Architecture, BI systems, MDM, and data governance. - Experience with agile methodologies and cross-functional team collaboration. - Excellent communication and presentation skills. As a Senior Data Architect, you will bring your expertise in data architecture, design, and development to drive the company's data infrastructure forward. Your role will be pivotal in shaping the future state data architecture, ensuring data quality, governance, and accessibility for actionable insights across the organization.,

As an AI Incubator Data Scientist at Barclays, you will embark on a transformative journey to spearhead the evolution of the digital landscape and drive innovation and excellence. Your role will involve harnessing cutting-edge technology to revolutionize digital offerings, ensuring unparalleled customer experiences. You will have the opportunity to shape and lead projects within the AI incubator team, leveraging machine learning techniques and AI to extract valuable insights and create tangible business impact. The position emphasizes a design-led thinking approach with close collaboration with business stakeholders and a fail-fast mindset. You will work with extensive datasets spanning billions of rows, applying state-of-the-art AI techniques to unlock millions in business value. **Key Responsibilities:** - Build relationships with senior stakeholders across the bank to identify opportunities for adding value through Data Science and GenAI. - Develop machine learning models and apply AI to deliver commercial value for the Corporate Bank. - Utilize AWS services for data transformation, feature engineering, AI product development, and deployment. - Communicate complex technical ideas to stakeholders through data visualization. - Collaborate with the ML Ops team in technology to streamline the path to production for successful projects. **Essential Skills and Qualifications:** - Bachelor's or master's degree in data science or equivalent commercial experience. - Experience working with senior stakeholders across the data science lifecycle, from idea inception to delivery in a production environment. - Ability to translate technical work into business terms and communicate value to business stakeholders. - Commercial experience in applying machine learning techniques for generating business value such as clustering, classification, regression, and NLP techniques. - Strong coding skills with a focus on Python and SQL, including a strong understanding of key coding principles like separation of concerns and generalization of code. - Familiarity with AWS data science and AI services, including SageMaker and Bedrock. - Proficiency in data visualization software, ideally Tableau, with exposure to QlikView, PowerBI, or similar tools. - Knowledge of code management methodologies and the ability to implement them on projects. **Desirable Skills/Preferred Qualifications:** - Experience in front-end development frameworks such as Angular/React Flask/Streamlit. - Knowledge of MVC Architecture. - Experience with Agentic AI and working in a big data environment using PySpark. In this role, you will use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves. Your insights will inform strategic decision-making, improve operational efficiency, and drive innovation across the organization. **Accountabilities:** - Identify, collect, and extract data from various sources, including internal and external sources. - Clean, wrangle, and transform data to ensure quality and suitability for analysis. - Develop and maintain efficient data pipelines for automated data acquisition and processing. - Design and conduct statistical and machine learning models to analyze patterns, trends, and relationships in the data. - Develop and implement predictive models to forecast future outcomes and identify risks and opportunities. - Collaborate with business stakeholders to add value from data through Data Science. In conclusion, as an AI Incubator Data Scientist at Barclays, you will play a pivotal role in driving innovation, leveraging cutting-edge technology, and extracting valuable insights to shape the digital landscape and deliver commercial value for the Corporate Bank.,

As a highly motivated and experienced data scientist, you will be leading a team of Gen-Ai Engineers involved in various processes from data extraction, cleaning, and pre-processing, to training models and deploying them to production. Your passion for artificial intelligence and staying up-to-date with the latest developments in the field will be crucial for success. Key Responsibilities: - Utilize frameworks like Langchain for developing scalable and efficient AI solutions. - Integrate vector databases such as Azure Cognitive Search, Weavite, or Pinecone to support AI model functionalities. - Collaborate with cross-functional teams to define problem statements and prototype solutions leveraging generative AI. - Ensure robustness, scalability, and reliability of AI systems by implementing best practices in machine learning and software development. - Explore and visualize data to gain insights and identify differences in data distribution that could impact model performance in real-world deployment. - Devise and oversee data-centered projects, verifying data quality, ensuring it through data cleaning, and supervising the data acquisition process if more data is needed. - Find and utilize available datasets for training, define validation strategies, feature engineering, and data augmentation pipelines. - Train models, tune hyperparameters, analyze model errors, and design strategies to overcome them. - Deploy models to production. Qualifications and Education Requirements: - Bachelors/Masters degree in computer science, data science, mathematics, or a related field. - 3-10 years of experience in building Gen-Ai applications. Preferred Skills: - Proficiency in statistical techniques for extracting insights and making predictions from data. - Experience with deep learning frameworks such as TensorFlow, PyTorch, and Keras. - Specialization in Deep Learning (NLP) and statistical machine learning. - Strong Python skills. - Experience in developing production-grade applications. - Familiarity with Langchain framework and vector databases like Azure Cognitive Search, Weavite, or Pinecone. - Understanding and experience with retrieval algorithms. - Worked on Big data platforms and technologies for processing and analyzing large volumes of data efficiently. - Familiarity with deploying applications on Ubuntu/Linux systems. - Excellent communication, negotiation, and interpersonal skills. Qualifications: - Bachelors/Masters degree in computer science, data science, mathematics, or a related field.,

As a Sr Data Engineer at Adobe, you will have the opportunity to contribute to all aspects of software coding and design, working closely with the Technical Manager and collaborating with Business Analysts to convert design specifications into database, ETL, or reporting solutions. Your role will involve system integration of data sources, developing user documentation and data flow diagrams, and delivering scalable solutions on the MSBI and Azure Cloud platform. Your expertise in SQL Server, SSIS, Azure Cloud Platform, TSQL, Databricks, Big Data, Gen AI technologies, scripting languages like DAX and Python, and database performance tuning will be crucial to your success in this role. Key Responsibilities: - System integration of heterogeneous data sources and working on technologies for DW & BI solutions - Develop and maintain user documentation, architecture designs, and data flow diagrams - Deliver scalable solutions on the MSBI and Azure Cloud platform - Implement source code versioning, standard methodology tools, and processes for ensuring data quality - Collaborate with business professionals, application developers, and technical staff in an agile process environment Qualifications Required: - Bachelor's in computer science or related streams - 5+ years of relevant work experience in SQL Server, SSIS, and Azure Cloud Platform (Azure SQL, ADF, DataBricks) - Proven working knowledge of TSQL, stored procedures, and database performance tuning - 5+ years of working experience in Databricks, Big Data, and Gen AI technologies - Proficient knowledge in scripting languages like DAX and Python - Ability to learn new software and technologies quickly and adapt to an ambitious and fast-paced environment,

As a Sr Data Engineer at Adobe, you will have the opportunity to work in a dedicated software design team, reporting directly to the Technical Manager. Your role will involve collaborating with Business Analysts to understand design specifications and translate requirements into database, ETL, or reporting solutions. Here's what you'll be doing: - Lead the integration of different data sources and contribute to the design, development, testing, deployment, and operations of Data Warehousing (DW) & Business Intelligence (BI) solutions. - Design and maintain user documentation, solution architecture, and data flow diagrams. - Deliver scalable, high-performance solutions using MSBI and the Azure Cloud platform. - Implement best practices for source code versioning, data quality, and performance optimization. - Collaborate with various stakeholders to deliver data-driven solutions in an agile environment. - Work with data science teams to operationalize Machine Learning (ML) models. - Drive improvements in data pipelines, automation, and modern data platform adoption. To succeed in this role, you will need: - A Bachelors degree in computer science, Engineering, or a related field. - 7+ years of relevant experience in Data Engineering with expertise in SQL Server and the Azure Cloud Platform (Azure SQL, ADF, Databricks). - Proficiency in T-SQL, stored procedures, and database performance tuning. - Hands-on experience with Databricks, Big Data platforms, and GenAI technologies. - Experience in supporting and deploying ML models, scripting/programming languages such as Python and DAX. - Strong problem-solving skills and the ability to learn quickly in a fast-paced environment. - Ability to mentor junior engineers and contribute to architectural decision-making. At Adobe, you will be part of a supportive work environment that values continuous growth and feedback. If you are looking to make a significant impact, Adobe is the place for you. Join us in creating exceptional digital experiences for everyone! Note: The additional details about the company were omitted as they were not relevant to the job description provided.,

As a Data Engineer at Veersa, you will be responsible for designing, developing, and implementing data pipelines using ETL tools like Informatica PowerCenter, IICS, etc., and MDM solutions using Informatica MDM. Your role will involve collaborating with data architects, business analysts, and stakeholders to understand data requirements, performing data profiling, data quality assessments, and master data matching/merging, and optimizing the performance of Informatica MDM Hub, IDD, and associated components. Additionally, you may need to write complex SQL queries and stored procedures as needed. **Key Responsibilities:** - Design, develop, and implement data pipelines using ETL tools like Informatica PowerCenter, IICS, etc., and MDM solutions using Informatica MDM. - Develop and maintain batch and real-time data integration workflows. - Collaborate with data architects, business analysts, and stakeholders to understand data requirements. - Perform data profiling, data quality assessments, and master data matching/merging. - Implement governance, stewardship, and metadata management practices. - Optimize the performance of Informatica MDM Hub, IDD, and associated components. - Write complex SQL queries and stored procedures as needed. **Required Qualifications:** For Software Engineer: - Bachelor's degree in Computer Science, Information Systems, or related field. - 2-4 years of experience with Informatica MDM (Customer 360, Business Entity Services, Match/Merge rules). - Strong SQL and data modeling skills. - Familiarity with ETL concepts, REST APIs, and data integration tools. - Understanding of data governance and quality frameworks. For Senior Software Engineer: - Bachelor's or Master's in Computer Science, Data Engineering, or related field. - 4+ years of experience in Informatica MDM, with at least 2 years in a lead role. - Proven track record of designing scalable MDM solutions in large-scale environments. - Strong leadership, communication, and stakeholder management skills. - Hands-on experience with data lakes, cloud platforms (AWS, Azure, or GCP), and big data tools is a plus.,

As an AI Incubator Data Scientist at Barclays, you will lead the evolution of the digital landscape, driving innovation and excellence by leveraging cutting-edge technology to enhance customer experiences. You will work within the Data Science team, particularly in the AI incubator, focusing on driving commercial value from data across the Corporate Bank. Your role will involve collaborating with senior stakeholders, developing machine learning models, applying AI to deliver commercial value, and leveraging AWS services for data transformation and AI product development. **Key Responsibilities:** - Build relationships with senior stakeholders to identify opportunities for adding value through Data Science and GenAI. - Develop machine learning models and apply AI to deliver commercial value for the Corporate Bank. - Utilize AWS services for data transformation, feature engineering, AI product development, and deployment. - Communicate complex technical ideas to stakeholders through data visualization. - Collaborate with the ML Ops team to streamline project production processes. **Essential Skills and Qualifications:** - Bachelor's or master's degree in data science or equivalent commercial experience. - Experience working with senior stakeholders throughout the data science lifecycle. - Ability to translate technical work into business terms and communicate value to stakeholders. - Commercial experience in applying machine learning techniques for business value. - Strong coding skills in Python and SQL, with an understanding of key coding principles. - Familiarity with AWS data science and AI services, including SageMaker and Bedrock. - Proficiency in data visualization software, especially Tableau, with exposure to other similar tools. - Knowledge of code management methodologies and their implementation in projects. **Desirable Skills/Preferred Qualifications:** - Experience in front-end development frameworks like Angular/React Flask/Streamlit. - Understanding of MVC Architecture and Agentic AI. - Experience working in a big data environment using PySpark. In this role, you will use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves. By leveraging these insights, you will inform strategic decision-making, improve operational efficiency, and drive innovation across the organization. As an Analyst, you are expected to perform activities in a timely manner with high standards, driving continuous improvement. You will lead and supervise a team, guide professional development, allocate work, and coordinate resources. Additionally, you will collaborate with other functions and business areas, take responsibility for managing risk and strengthening controls, and advise decision-making within your area of expertise. All colleagues at Barclays are expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence, and Stewardship, as well as the Barclays Mindset to Empower, Challenge, and Drive. As an AI Incubator Data Scientist at Barclays, you will lead the evolution of the digital landscape, driving innovation and excellence by leveraging cutting-edge technology to enhance customer experiences. You will work within the Data Science team, particularly in the AI incubator, focusing on driving commercial value from data across the Corporate Bank. Your role will involve collaborating with senior stakeholders, developing machine learning models, applying AI to deliver commercial value, and leveraging AWS services for data transformation and AI product development. **Key Responsibilities:** - Build relationships with senior stakeholders to identify opportunities for adding value through Data Science and GenAI. - Develop machine learning models and apply AI to deliver commercial value for the Corporate Bank. - Utilize AWS services for data transformation, feature engineering, AI product development, and deployment. - Communicate complex technical ideas to stakeholders through data visualization. - Collaborate with the ML Ops team to streamline project production processes. **Essential Skills and Qualifications:** - Bachelor's or master's degree in data science or equivalent commercial experience. - Experience working with senior stakeholders throughout the data science lifecycle. - Ability to translate technical work into business terms and communicate value to stakeholders. - Commercial experience in applying machine learning techniques for business value. - Strong coding skills in Python and SQL, with an understanding of key coding principles. - Familiarity with AWS data science and AI services, including SageMaker and Bedrock. - Proficiency in data visualization software, especially Tableau, with exposure to other similar tools. - Knowledge of code management methodologies and their implementation in projects. **Desirable Skills/Preferred Qualifications:** - Experience in front-end development frameworks like Angular/Rea

As a Data Analyst with 5+ years of experience, you will need to have extensive experience with BigQuery, with a minimum of 2 years of hands-on work in this area. Your role will involve utilizing your strong communication skills to effectively convey insights derived from data analysis. **Key Responsibilities:** - Utilize your 5+ years of experience as a Data Analyst to extract valuable insights from data. - Demonstrate a minimum of 2 years of in-depth experience with BigQuery. - Communicate effectively with stakeholders to share findings and recommendations. **Qualifications Required:** - Proven track record as a data analyst for at least 5 years. - Minimum of 2 years of hands-on experience with BigQuery. - Excellent communication skills to convey complex data insights clearly.,

As an Assistant Director - AI/GenAI at EY, you will be responsible for developing and delivering industry-specific solutions using Artificial Intelligence, Machine Learning, deep learning, and LLM models for Generative AI, text analytics, and Python programming. Your role will involve leading the development and implementation of Generative AI applications, working with advanced models like GPT-3.5, GPT 4, Llama, BERT, and optimizing solutions leveraging Vector databases for efficient storage and retrieval of contextual data for LLMs. You will also work on identifying opportunities for analytics applications, managing projects, and ensuring smooth service delivery. **Key Responsibilities:** - Develop, review, and implement solutions applying AI, Machine Learning, and Deep Learning - Lead the development and implementation of Generative AI applications - Work with advanced models for natural language processing and creative content generation - Design and optimize solutions leveraging Vector databases - Understand business sectors and identify opportunities for analytics application - Manage projects and ensure smooth service delivery - Communicate with cross-functional teams - Go-to-market/stakeholder management **Qualifications Required:** - Experience guiding teams on AI/Data Science projects - Familiarity with implementing solutions in Azure Cloud Framework - Excellent presentation skills - 12-16 years of relevant work experience in developing and implementing AI, Machine Learning Models - Experience with statistical techniques, deep learning, and machine learning algorithms - Proficiency in Python programming - Familiarity with software development life cycle (SDLC) - Willingness to mentor team members As an ideal candidate, you should have the ability to think strategically, build rapport within the firm, and travel extensively. EY offers opportunities to work with a global team of professionals in a dynamic and inclusive culture, providing continuous learning and transformative leadership. Join EY and be a part of building a better working world through innovation and collaboration across industries and geographies.,

As a Technical Architect, you will be responsible for designing and implementing full-stack applications using a variety of front-end and back-end technologies. Your expertise in front-end technologies such as HTML5, CSS3, and JavaScript, along with proficiency in frameworks like React, Angular, or Vue.js, will be crucial in developing user-friendly interfaces. Additionally, your strong back-end development skills in languages like Java, Python, or Node.js will enable you to build robust server-side components. Key Responsibilities: - Develop full-stack applications by leveraging server-side technologies and frameworks such as Spring or Express.js - Utilize database expertise in SQL and NoSQL databases like MySQL, PostgreSQL, or MongoDB for efficient data storage and retrieval - Implement RESTful and GraphQL APIs to create scalable and efficient applications - Ensure version control using Git and collaborate effectively using platforms like GitHub or GitLab - Architect and design scalable and resilient systems while adhering to security best practices Qualifications Required: - Proven track record of developing full-stack applications in a professional setting - Experience with Agile and Scrum methodologies and the ability to work in multi-functional teams - Knowledge of software development standard methodologies, including code reviews, testing, and documentation - Familiarity with cloud computing platforms like AWS, Azure, or Google Cloud and serverless architectures - Proficiency in DevOps practices, CI/CD pipelines, and infrastructure as code - Security awareness and understanding of standard methodologies for securing web applications and data Additionally, experience with AI, particularly Generative AI, and mobile app development for iOS/Android would be advantageous in this role. Please note that the job is full-time and permanent, and the preferred experience for this position is 10 years as a Technical Architect. The work location is in person.,

Role Overview: You are seeking an experienced Senior Big Data Cloud Quality Assurance Engineer to join a dynamic team. Your role involves ensuring the quality and performance of big data applications and services deployed in cloud environments. You will collaborate with developers, product managers, and stakeholders to define testing strategies, develop test plans, and execute comprehensive testing processes. Key Responsibilities: - Design and implement test plans and test cases for big data applications in cloud environments. - Perform functional, performance, and scalability testing on large datasets. - Identify, record, and track defects using bug tracking tools. - Collaborate with development teams to understand product requirements and provide feedback on potential quality issues early in the development cycle. - Develop and maintain automated test scripts and frameworks for continuous integration and deployment. - Analyze test results and provide detailed reports on the quality of releases. - Mentor junior QA team members and share best practices in testing methodologies and tools. - Stay updated on industry trends and advancements in big data and cloud technologies to continuously improve QA processes. Qualifications: - Bachelor's degree in Computer Science, Information Technology, or a related field. - Minimum of 5 years of experience in software testing, with at least 2 years focused on big data applications and cloud technologies. - Proficiency in testing frameworks and tools, such as JUnit, TestNG, Apache JMeter, or similar. - Experience with big data technologies, such as Hadoop, Spark, or distributed databases. - Strong understanding of cloud platforms, such as AWS, Azure, or Google Cloud. - Familiarity with programming languages such as Java, Python, or Scala. - Excellent analytical and problem-solving skills with attention to detail. - Strong communication skills, both verbal and written, with the ability to work collaboratively in a team environment. If you are a motivated and detail-oriented professional looking to advance your career in big data quality assurance, you are encouraged to apply for this exciting opportunity.,

As an Azure Data Engineer at EY, you will be part of a globally connected powerhouse of diverse teams, where you will have the opportunity to shape your future with confidence. EY is a leading global professional services firm that offers a broad range of services in assurance, tax, transaction, and advisory services. Your role will be crucial in contributing to the betterment of the working world by leveraging your expertise in technology and data engineering. **Key Responsibilities:** - Develop and deploy Azure Databricks in a cloud environment using Azure Cloud services. - Design, develop, and deploy ETL processes in Azure Data Factory. - Collaborate with Onshore teams, understand their business goals, and contribute to the delivery of workstreams. - Design and optimize model codes to ensure faster execution. **Skills And Attributes For Success:** - 4 to 7 years of experience in developing data ingestion, data processing, and analytical pipelines for big data, relational databases, NoSQL, and data warehouse solutions. - Extensive hands-on experience in implementing data migration and processing using Azure services such as Databricks, ADLS, Azure Data Factory, Azure Functions, Synapse/DW, Azure SQL DB, Azure Data Catalog, and Cosmo Db. - Proficiency in Spark and programming languages like Python or Scala. - Strong knowledge of DevOps and CI/CD deployments. - Hands-on experience in SQL and procedural SQL languages. - Strong analytical skills with a passion for solving complex technical problems. **Qualification Required:** - Working experience in an Agile-based delivery methodology is preferable. - Proactive and self-motivated working style with a strong sense of ownership in problem resolution. - Excellent debugging and optimization skills. - Experience in enterprise-grade solution implementations and transforming business challenges into technical solutions considering security, performance, and scalability factors. - Excellent communication skills, both written and verbal, for formal and informal settings. - Proficiency in all aspects of the solution delivery lifecycle, including analysis, design, development, testing, production deployment, and support. **Education:** - BS/MS degree in Computer Science, Engineering, or a related subject is required. EY is committed to providing equal opportunities to all candidates and encourages applications from individuals with diverse experiences and backgrounds. Join EY in building a better working world by leveraging data, AI, and advanced technology to shape the future with confidence and address the most pressing issues of today and tomorrow. With a globally connected network and ecosystem partners, EY teams operate in over 150 countries and territories to deliver a full spectrum of services in assurance, consulting, tax, strategy, and transactions.,