206 Data Warehousing Jobs in Hyderabad

Job Title: GCP Data Engineer Employment Type: Permanent Industry of the Employer: IT / Software Services Department / Functional Area: Data Engineering, Cloud Engineering Job Description GREETINGS FROM HUCON Solutions Hiring for Leading MNC GCP Data Engineer Role: GCP Data Engineer Skills: GCP, Python, SQL, BigQuery, ETL Data Pipeline Experience: 59 Years Locations: Chennai, Kochi, Bangalore, Hyderabad, Pune Eligibility Criteria Strong hands-on experience in Python, Pandas, NumPy Expertise in SQL and solid understanding of Data Warehousing concepts In-depth knowledge of GCP Services including: BigQuery, Cloud Run, Pub/Sub, Cloud Storage, Spanner, Cloud Composer, Dataflow, Cloud Functions Experience with Docker, Kubernetes, GitHub Strong communication and analytical skills Working experience with PySpark, Data Modeling, Dataproc, Terraform Google Cloud Professional Data Engineer certification is highly preferred Role Responsibilities Design, develop, and manage robust and scalable ETL / ELT pipelines on GCP using Dataflow, Cloud Run, BigQuery, Pub/Sub, and Cloud Composer Implement data ingestion workflows for structured and unstructured data sources Build and maintain data warehouses and data lakes using BigQuery, Cloud Storage, and other GCP tools Work with data modeling, architecture, and ETL/ELT frameworks Ensure best practices in performance, optimization, and cloud data management Keywords / Skills GCP, Python, SQL, BigQuery, ETL, Data Pipeline, Data Engineering, Cloud Run, Pub/Sub, Cloud Storage, Dataproc, Terraform, Kubernetes, Docker, Dataflow Total Experience: 5 to 9 Years Salary Type: Yearly Annual Salary Offered: As per company standards Job Type: Full Time Shift Type: Day Shift / Rotational (based on project requirement) Location of the Job: Chennai | Kochi | Bangalore | Hyderabad | Pune

About the Role We are seeking a highly skilled Senior Data Engineer with deep expertise in Snowflake and strong proficiency in SQL to join our Data Insights Engineering team The ideal candidate should have handson experience designing and building scalable data pipelines optimizing data warehouses and enabling advanced analytics This role requires strong data engineering fundamentals experience in Pythonbased ETLELT development and working knowledge of BI tools like Tableau to support business stakeholders Key Responsibilities Design develop and maintain data pipelines and workflows on Snowflake Write highly optimized SQL queries transformations and stored procedures for complex data engineering use cases Architect and implement data models schemas and warehouse structures that support analytics and reporting Integrate data from multiple sources databases APIs files streaming into Snowflake using PythonETL frameworks Optimize Snowflake performance warehouses caching clustering partitioning cost control Partner with analysts and business teams to deliver clean reliable datasets for Tableau and other reporting tools Implement data quality checks monitoring and ing for critical pipelines Collaborate with crossfunctional teams Data Scientists Analysts Product Engineering Contribute to best practices in data governance documentation and security Required Skills Experience 7 years of handson Data Engineering experience Strong expertise in Snowflake warehouses roles RBAC tasks streams procedures Snowpark a plus Expertlevel SQL query optimization advanced analytics functions performance tuning Proficiency in Python for ETL ELT scripting and automation Experience with Tableau for dashboarding and data validation Solid knowledge of data modeling data warehousing concepts and ELT pipelines Strong understanding of cloud data platforms AWS preferred Familiarity with CICD Git Docker and orchestration tools Airflow dbt etc

Senior Snowflake Data Engineer Location: PAN India Experience: 8+ Years Skills: Snowflake, dbt, FiveTran, Snowpipe, AWS (MWAA, S3, Lambda), GitHub CI/CD Job Description We are looking for an experienced Senior Snowflake Data Engineer with strong expertise in modern data warehousing, cloud technologies, and ELT pipeline development. The ideal candidate should have deep hands-on experience in Snowflake, dbt, cloud environments, and CI/CD practices, with the ability to design scalable and efficient data solutions. Key Responsibilities Analyze, integrate, model, and interpret large and complex datasets from multiple sources. Design and implement ELT data pipelines using dbt with Snowflake as the primary cloud data warehouse. Build efficient and scalable data transformation pipelines using dbt at an advanced level. Work with ETL/ELT and data governance tools such as FiveTran and Alation. Utilize advanced Snowflake features such as RBAC, Dynamic Tables, and various optimization techniques. Ensure strong data modelling and warehousing practices across diverse database technologies. Manage orchestrations using Apache Airflow or AWS MWAA, along with CI/CD pipelines. Oversee continuous deployment, monitoring, and operations of data solutions using GitHub Actions, Terraform, and other DevOps tools. Collaborate with technical and non-technical stakeholders through effective communication. Contribute to building future-state Data Warehouse capabilities using cutting-edge technologies. Adapt and work efficiently within Agile methodology. Preferred Qualifications 2+ years of hands-on experience with Snowflake as a Cloud Data Warehouse and Data Lake platform. Strong understanding of cloud environments, especially AWS (S3, Lambda, MWAA). Airline industry domain experience is a plus.

Job Description We are seeking an experienced Snowflake Database Administrator DBA to join our team The ideal candidate will have a deep understanding of Data Warehousing fundamentals and concepts with a proven track record in Snowflake administration Key Responsibilities Database Management Oversee and manage Snowflake databases including user management security management performance tuning high availability space management and backuprecovery processes Automation Implement and support automation for production deployments in Snowflake Automate database administration tasks using PLSQL shell scripts and other relevant scripting languages Troubleshooting Diagnose and resolve Snowflake database errors ensuring minimal downtime and disruption to services Security Implement and enforce data encryption decryption and masking policies to protect sensitive PIIPCI data Conduct regular user security audits to ensure compliance with organizational policies Performance Optimization Demonstrate proficiency in index design query plan optimization and analysis to enhance database performance Tune Snowflake databases to optimize query performance Capacity Planning Create and maintain Snowflake utilization and capacity plans to ensure efficient resource usage and scalability Scripting and Automation Develop scripts and workflows using languages such as Python and PowerShell as well as automation tools like Ansible and Terraform to streamline database provisioning configuration and maintenance tasks Monitoring and ing Implement automated monitoring and ing systems to proactively identify and address performance issues security vulnerabilities and other databaserelated concerns Qualifications Snowflake DBA AWS SQL ETL concepts Airflow or any orchestration tools Data Warehousing concepts Proficiency in scripting languages eg Python Shell and automation tools eg Ansible Terraform Experience in database performance tuning security management and automation Ability to diagnose and troubleshoot database issues effectively Excellent problemsolving and communication skills

As a Big Data Engineer with Gen AI, you will be responsible for the following: - Hands-on experience with Kafka/Kinesis for real-time data processing. - Strong SQL skills with a background in database design and data modeling. - Proficiency in working with Hadoop, Hive, and Spark (PySpark/Scala). - Comprehensive understanding of data warehousing, ETL processes, data migration, and integration. - Knowledge of Big Data technologies and distributed computing. - Exposure to GenAI/ML frameworks such as TensorFlow, PyTorch, prompt engineering, and RAG models. - Experience in cloud architecture, CI/CD pipelines, and automation. Please note that the job location for this position includes Hyderabad, Bangalore, NCR, and Pune with a notice period of 30 days.,

Role Overview: You will be responsible for designing, building, and optimizing modern data platforms as a Senior Data Analytics/Engineer. Your expertise in Python, Snowflake, Databricks, and SQL will be crucial for leading data engineering initiatives and contributing to high-impact analytics projects. You will also play a key role in driving best practices across the organization. Key Responsibilities: - Design, develop, and maintain scalable data pipelines and workflows using Python, Snowflake, and Databricks. - Build and automate ELT/ETL processes while following best practices in data modeling and transformation. - Develop transformation models with DBT Core to standardize and streamline data operations. - Optimize large-scale datasets for performance, reliability, and accessibility. - Write advanced, high-performance SQL queries for data extraction, transformation, and analysis. - Implement and manage CI/CD workflows using GitHub Actions for automated testing, deployment, and version control. - Collaborate with data analysts, data scientists, and business stakeholders to deliver high-quality data solutions. - Ensure data integrity, security, and governance across platforms. - Troubleshoot complex data issues and implement long-term automation and monitoring solutions. - Stay updated with emerging data engineering tools and best practices. Qualification Required: - 5+ years of experience in Data Engineering or Senior Data Analytics roles. - Strong proficiency in Python for data engineering and automation. - Hands-on experience with Snowflake and Databricks environments. - Expert-level SQL skills and experience working with large datasets. - Experience with DBT Core (highly preferred). - Experience in implementing CI/CD pipelines using GitHub Actions. - Solid understanding of data warehousing, data modeling (e.g., Kimball, Data Vault), and ETL/ELT principles. - Familiarity with cloud platforms like AWS, Azure, or GCP. - Strong problem-solving abilities and capability to work independently in a fast-paced environment. Preferred Qualifications: - Experience with infrastructure-as-code or automation tools. - Knowledge of testing frameworks for data validation (e.g., Great Expectations). - Experience working in an agile environment.,

Role Overview: As a Big Data & Data Engineering Module Lead with 5+ years of experience, your main responsibility will be to work with SnapLogic in at least one project and have hands-on experience in Snowflake. Additionally, you will be expected to have expertise in ETL tools like Datastage, strong knowledge in ETL, Data Modelling, Data warehousing, SQL, PL/SQL, and RDBMS. Your role will involve designing, developing, and deploying reliable solutions, working with business partners to provide lasting solutions, configuring clustered and distributed scalable parallel environments, having cloud platform knowledge (AWS or Azure), and proficiency in Python / Pyspark. You should also have knowledge in job controlling/scheduling tools with batch programming skills, the ability to work with developers and lead them to successful job completion, good analytical and troubleshooting skills, as well as excellent communication and strong interpersonal skills. Key Responsibilities: - Work with SnapLogic in at least one project - Hands-on experience in Snowflake - Experience with ETL tools like Datastage - Strong knowledge in ETL, Data Modelling, and Data warehousing - Proficiency in SQL, PL/SQL, and RDBMS - Design, develop, and deploy reliable solutions - Collaborate with business partners to provide long-lasting solutions - Configure clustered and distributed scalable parallel environments - Knowledge in cloud platforms like AWS or Azure - Proficiency in Python / Pyspark is preferred - Knowledge in job controlling/scheduling tools with batch programming skills - Work with developers and lead them in successful job completion - Strong analytical and troubleshooting skills - Excellent communication and strong interpersonal skills Qualifications Required: - 5+ years of experience in Big Data & Data Engineering - Hands-on experience with SnapLogic - Knowledge in Snowflake and ETL tools like Datastage - Strong understanding of ETL, Data Modelling, and Data warehousing - Proficiency in SQL, PL/SQL, and RDBMS - Experience in designing, developing, and deploying reliable solutions - Ability to work with business partners and provide long-lasting solutions - Knowledge in configuring clustered and distributed scalable parallel environments - Familiarity with cloud platforms like AWS or Azure - Proficiency in Python / Pyspark preferred - Understanding of job controlling/scheduling tools with batch programming skills - Ability to work with developers and lead them to successful job completion - Strong analytical and troubleshooting skills - Excellent communication and strong interpersonal skills,

As a Data Engineer at our company, you will be responsible for designing, developing, and maintaining scalable and efficient data pipelines using GCP services such as Dataflow, Cloud Composer (Airflow), and Pub/Sub. Your role will involve designing and implementing robust data models optimized for analytical and operational workloads within GCP data warehousing solutions like BigQuery. Additionally, you will develop and implement ETL processes to ingest, cleanse, transform, and load data from various sources into the data warehouse and other data stores on GCP. Key Responsibilities: - Build and manage data warehousing solutions on GCP, ensuring data integrity, performance, and scalability. - Collaborate with data scientists and analysts to understand their data requirements and provide them with clean, transformed, and readily accessible data. - Monitor and troubleshoot data pipelines and data warehousing systems to ensure data quality and availability. - Implement data quality checks and validation processes to maintain the accuracy and reliability of data. - Optimize data processing and storage for performance and cost-efficiency on the GCP platform. - Stay up-to-date with the latest GCP data services and best practices in data engineering and analytics. - Contribute to the documentation of data pipelines, data models, and ETL processes. - Work collaboratively with cross-functional teams to understand data needs and deliver effective data solutions. Qualifications: - Bachelor's degree in Computer Science, Engineering, or a related field. - Proven experience in data engineering principles and practices. - Solid understanding of data modeling concepts and techniques (e.g., relational, dimensional). - Hands-on experience in designing, developing, and implementing ETL processes. - Knowledge of data warehousing concepts, architectures, and best practices. - Familiarity with data analytics principles and the data lifecycle. - Strong problem-solving and analytical skills with the ability to troubleshoot data-related issues. - Excellent communication and collaboration skills. Preferred Qualifications (A Plus): - Hands-on experience working with Google Cloud Platform (GCP) data services such as BigQuery, Dataflow, Cloud Composer (Airflow), Pub/Sub, Cloud Storage, etc. - Experience with scripting languages such as Python or SQL for data manipulation and automation. - Familiarity with data visualization tools (e.g., Looker, Tableau). - Experience with data governance and data security principles. - Knowledge of DevOps practices and tools for data infrastructure automation.,

Role Overview: As a Data Engineer-AIML at the company in India, you will play a crucial role in building and maintaining data architectures to support AIML initiatives. Your primary responsibilities will include: Key Responsibilities: - Designing, developing, and maintaining scalable data pipelines for efficient data ingestion and processing. - Collaborating closely with data scientists and analysts to understand data requirements and ensure high data quality. - Implementing and optimizing ETL processes to improve data retrieval and storage efficiency. - Developing and managing data models and architecture specifically for AIML applications. - Conducting data analysis to extract insights that can support key business decisions and strategies. - Monitoring and troubleshooting data pipeline performance to maintain high availability and reliability. Qualifications Required: - Proficiency in programming languages such as Python, Java, or Scala. - Experience with big data technologies like Hadoop, Spark, or Kafka. - Strong knowledge of SQL and relational databases such as PostgreSQL or MySQL. - Familiarity with cloud platforms like AWS, Azure, or Google Cloud. - Hands-on experience with data warehousing solutions and data modeling. - Understanding of machine learning concepts and frameworks, such as TensorFlow or PyTorch (a plus). - Ability to work with version control systems like Git. - Strong problem-solving skills and the flexibility to work both independently and as part of a team.,

As a Staff Software Engineer in the Data Quality & Audience team at Warner Bros. Discovery, you will play a crucial role in maintaining data quality and facilitating data-driven decisions. Your technical expertise will be vital in developing systems that adhere to quality standards and in creating datasets using top-notch software engineering and data management practices. Your responsibilities will include: - Applying comprehensive knowledge of technology options within the Data Engineering ecosystem - Constructing systems and datasets while adhering to best practices and operational excellence - Grasping data warehousing concepts, ETL processes, and tools such as Apache Airflow and Talend - Proficiency in SQL for data querying and validation across various databases - Familiarity with programming languages like Python or R for data manipulation and automation - Expertise in ensuring data quality, integrity, and consistency in datasets - Knowledge of data quality tools like Apache Spark, Pandas, and Great Expectations - Experience with big data frameworks like Hadoop and Apache Spark - Proficiency in testing and validating data flows through APIs and web services - Understanding automation workflows, CICD release pipelines, and test environments - Leading the design, execution, and upkeep of automated tests to guarantee data products meet standards - Providing guidance by mentoring fellow engineers and sharing knowledge to enhance workforce capabilities - Communicating effectively through technical documentation, commented code, and engaging with stakeholders Warner Bros. Discovery provides an inclusive work environment with equal opportunities for all employees and avenues for rapid career growth. The company's guiding principles are fundamental values that govern its operations. To learn more about these guiding principles and their impact on daily operations, visit www.wbd.com/guiding-principles/. If you are a qualified candidate with a disability and require accommodations during the application process, please refer to our accessibility page for guidance on submitting your request.,

As an experienced Data Engineer, your role will involve designing, building, and optimizing scalable data pipelines and solutions using various technologies within the Azure Data Services ecosystem, Python, PySpark, and databases. Your responsibilities will include: - Designing, developing, and maintaining data pipelines using Azure Data Factory (ADF) and Databricks. - Working with Azure Data Lake Storage (ADLS), Microsoft Fabric, and Azure Synapse Analytics to build robust data platforms. - Developing scalable ETL/ELT solutions leveraging Python, PySpark, and SQL. - Optimizing data workflows for performance, reliability, and cost efficiency. - Collaborating with data scientists, analysts, and business teams to ensure data availability and quality. - Implementing best practices for data governance, security, and compliance in the Azure ecosystem. - Monitoring, troubleshooting, and enhancing data processes and pipelines in production environments. - Staying current with evolving Azure cloud technologies, big data frameworks, and modern data architectures. Your skills and qualifications should include: - Strong experience with Azure Data Services such as Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Microsoft Fabric, and Azure Synapse Analytics. - Expertise in Databricks for data engineering and analytics. - Proficiency in Python and PySpark for large-scale data processing. - Strong knowledge of SQL and relational/non-relational databases. - Experience with data modeling, ETL/ELT pipelines, and data warehousing concepts. - Understanding of CI/CD, version control (Git), and DevOps practices. - Excellent problem-solving, communication, and collaboration skills. Preferred qualifications may include: - Experience with data governance frameworks and security best practices in Azure. - Knowledge of machine learning integration within Databricks. - Familiarity with Power BI or other visualization tools. - Prior experience in agile environments. In terms of education and experience, a Bachelors or Masters degree in Computer Science, Information Systems, Data Engineering, or related field along with 3+ years of professional experience in data engineering or big data roles would be preferred.,

Role Overview: As a Data Lead at LERA Technologies, you will have the opportunity to own the data strategy, architecture, and engineering roadmap for key client engagements. Your role involves leading the design and development of scalable, secure, and high-performance data pipelines, marts, and warehouses. You will also be responsible for mentoring a team of data engineers, collaborating with BI/reporting teams and solution architects, and overseeing data ingestion, transformation, consolidation, and validation across cloud and hybrid environments. Championing best practices for data quality, data lineage, and metadata management, evaluating emerging tools, technologies, and frameworks to enhance platform capabilities, engaging with business and technical stakeholders to translate analytics needs into scalable data solutions, and monitoring performance to optimize storage and processing layers for efficiency and scalability. Key Responsibilities: - Own the data strategy, architecture, and engineering roadmap for key client engagements - Lead design and development of scalable, secure, and high-performance data pipelines, marts, and warehouses - Mentor a team of data engineers and collaborate with BI/reporting teams and solution architects - Oversee data ingestion, transformation, consolidation, and validation across cloud and hybrid environments - Champion best practices for data quality, data lineage, and metadata management - Evaluate emerging tools, technologies, and frameworks to enhance platform capabilities - Engage with business and technical stakeholders to translate analytics needs into scalable data solutions - Monitor performance and optimize storage and processing layers for efficiency and scalability Qualifications Required: - 7+ years of experience in Data Engineering, including SQL/PLSQL/TSQL, ETL development, and data pipeline architecture - Strong command of ETL tools (SSIS or equivalent) and Data Warehousing concepts - Expertise in data modeling, architecture, and integration frameworks - Experience leading data teams and managing end-to-end data delivery across projects - Hands-on knowledge of BI tools (Power BI/Tableau/SAP BO/OBIEE) and their backend integration - Proficiency in big data technologies and cloud platforms (Azure, AWS, or GCP) - Programming experience in Python, Java, or equivalent languages - Proven experience in performance tuning and optimization of large datasets - Strong understanding of data governance, data security, and compliance best practices - Excellent communication, stakeholder management, and team mentoring abilities Join LERA Technologies and embrace innovation, creativity, and experimentation with the I.C.E. Philosophy. Make a significant impact on clients" success across various industries while thriving in a workplace that values diversity and inclusive excellence. Benefit from extensive opportunities for professional growth and career advancement. Apply now to lead cutting-edge projects with an agile and visionary team at LERA Technologies.,

As an AWS Cloud Data Architect, you will play a crucial role in the Data Products Solutions Architecture Team. Your primary responsibility will be to design and implement scalable analytical data solutions that are in line with the strategic objectives of the organization. Key Responsibilities: - Represent the data product solutions architecture team in various forums, providing expert advice on data product solutions. - Collaborate with cross-functional teams to ensure that data product solutions meet business requirements and facilitate data-driven decision-making. - Act as a subject matter expert in areas like complex large-scale migration with platform and system differences. - Contribute to the data engineering community and promote firmwide data practices. - Engage in hands-on coding and design to implement production solutions. - Optimize system performance by addressing inefficiencies effectively. Qualifications Required: - 10+ years of experience with at least 5 years in a Data product solution Architect or similar leadership role, overseeing technologists in managing, anticipating, and resolving complex technical tasks. - Hands-on experience in system design, application development, and ensuring operational stability. - Expertise in Architecture disciplines and proficiency in programming languages. - Deep understanding of data architecture, integration, cloud data services, best practices for large scale migration, etc. - Practical experience with AWS big data technologies and various data engineering disciplines. - Advanced experience in one or more data engineering disciplines such as streaming, ELT/ELT, event processing. - Proficiency in SQL and familiarity with data warehousing solutions using Teradata or similar cloud-native relational databases like Snowflake, Postgres. - Strong problem-solving abilities, along with excellent communication and interpersonal skills. - Capability to assess and recommend technologies for the future state architecture.,

Role Overview: As a software engineer at Google, you will be developing the next-generation technologies that impact how billions of users connect, explore, and interact with information and each other. You will work on critical projects that cater to Google's needs, with the opportunity to switch teams and projects as both you and the fast-paced business evolve. Your role will involve handling information at massive scale and contributing to various areas such as information retrieval, distributed computing, system design, networking, security, artificial intelligence, UI design, and more. Key Responsibilities: - Develop big data pipelines with over 250 billion rows and report solutions ensuring low tolerances for data error. - Create data platform tooling for environment management, data management, pipeline alerting/monitoring, and data reconciliation. - Lead the design, data modeling, architecture, coding, performance tuning, testing, and support of analytical systems, taking ownership of the Software Development Life Cycle (SDLC) cycle. - Maintain development practices including technical design, solution development, systems configuration, test documentation/execution, issue resolution, and write modular and self-sustaining code. - Act as a site lead for a team. Qualifications Required: - Bachelor's degree or equivalent practical experience. - 8 years of experience with one or more general-purpose programming languages such as Java, C/C++, or Python. - 5 years of experience in testing and launching software products. - 8 years of experience with data structures and algorithms. - Experience working with big data platforms like BigQuery, F1, or Spanner. - Knowledge of data warehousing concepts and best practices.,

As a Finance Data Analyst at Model N, you will be an integral part of the Business Intelligence (BI) team in India. Your role will involve partnering closely with U.S. Finance and other cross-functional teams to provide data-driven insights that aid in financial planning, forecasting, and performance management. Your strong analytical, technical, and business acumen will play a key role in transforming data into actionable insights. Key Responsibilities: - Collaborate with Finance and cross-functional teams to translate business inquiries into clear, data-driven insights supporting planning, forecasting, and performance management. - Lead end-to-end analytics projects by defining requirements, exploring financial and operational datasets, building data models, and presenting insights through dashboards, reports, and presentations. - Develop, enhance, and maintain Power BI dashboards to track key financial and go-to-market metrics. - Analyze customer, revenue, and product data to identify trends informing strategic decision-making. - Assist in developing predictive or statistical models using Python or similar tools. - Validate data accuracy and reconcile financial and operational metrics across various sources. - Utilize SQL, Python, and cloud data tools to prepare datasets, automate workflows, and scale financial analytics processes. - Ensure alignment on KPI definitions, data sources, and metric governance to drive consistent reporting. - Continuously enhance analytics workflows, data visualization standards, and self-service reporting capabilities. Qualifications Required: - 5-8 years of experience in business intelligence, data analytics, or related roles. - Proven track record of delivering actionable insights from complex datasets. - Experience collaborating cross-functionally to support strategic initiatives. - Bachelor's degree in a quantitative, technical, or business field; Master's degree preferred. Additional Company Details: Model N may incorporate artificial intelligence (AI) tools in the hiring process to support recruitment activities. These tools aid the recruitment team but do not replace human judgment, as final hiring decisions are made by humans. For more information on data processing, feel free to reach out to us.,

Role Overview: As a Data Lead at LERA Technologies, you will be responsible for owning the data strategy, architecture, and engineering roadmap for key client engagements. Your role involves leading the design and development of scalable, secure, and high-performance data pipelines, marts, and warehouses. You will mentor a team of data engineers, collaborate with BI/reporting teams and solution architects, oversee data ingestion, transformation, consolidation, and validation across cloud and hybrid environments, and champion best practices for data quality, data lineage, and metadata management. Additionally, you will evaluate emerging tools, technologies, and frameworks to enhance platform capabilities and engage with business and technical stakeholders to translate analytics needs into scalable data solutions. Your responsibilities also include monitoring performance and optimizing storage and processing layers for efficiency and scalability. Key Responsibilities: - Own the data strategy, architecture, and engineering roadmap for key client engagements - Lead design and development of scalable, secure, and high-performance data pipelines, marts, and warehouses - Mentor a team of data engineers and collaborate with BI/reporting teams and solution architects - Oversee data ingestion, transformation, consolidation, and validation across cloud and hybrid environments - Champion best practices for data quality, data lineage, and metadata management - Evaluate emerging tools, technologies, and frameworks to enhance platform capabilities - Engage with business and technical stakeholders to translate analytics needs into scalable data solutions - Monitor performance and optimize storage and processing layers for efficiency and scalability Qualifications Required: - 7+ years of experience in Data Engineering, including SQL/PLSQL/TSQL, ETL development, and data pipeline architecture - Strong command of ETL tools (SSIS or equivalent) and Data Warehousing concepts - Expertise in data modeling, architecture, and integration frameworks - Experience leading data teams and managing end-to-end data delivery across projects - Hands-on knowledge of BI tools (Power BI/Tableau/SAP BO/OBIEE) and their backend integration - Proficiency in big data technologies and cloud platforms (Azure, AWS, or GCP) - Programming experience in Python, Java, or equivalent languages - Proven experience in performance tuning and optimization of large datasets - Strong understanding of data governance, data security, and compliance best practices - Excellent communication, stakeholder management, and team mentoring abilities Additional Company Details: LERA Technologies follows the I.C.E. Philosophy, embracing Innovation, Creativity, and Experimentation. Employees at LERA Technologies significantly impact clients" success across various industries. The company culture values diversity and inclusive excellence, providing employees with a workplace where they can thrive. Professional growth opportunities are extensive at LERA Technologies, offering employees benefits from career advancement prospects. Join LERA Technologies and lead data-driven transformation as a Data Lead, contributing to shaping the future of enterprise data. Apply now to work on cutting-edge projects with an agile and visionary team.,

As a Senior Associate of Investment Data and Reporting at Oaktree, your role will be crucial in overseeing the curation of deal data throughout the investment life cycle, with a focus on credit instruments and markets. You will work closely with deal teams, administrative agents, and middle and back-office teams to ensure accurate and standardized data is captured for internal systems and reporting tools. Your responsibilities will include: - Data Validation and Exception Management: - Spread borrower financials and validate using automation tools. - Prepare monitoring outputs, track valuations, and provide sector-specific KPIs and commentary. - Analyze covenant terms to extract and standardize relevant data. - Streamline data capture for portfolio monitoring, loan administration, valuation, and reporting. - Technology-enabled Reporting: - Utilize Python, SQL, and data visualization tools to manage and manipulate large datasets. - Create standardized reports or dashboards to support decision-making processes. - Partnership & Innovation: - Collaborate with various organizational partners to ensure robust data production and advancement of RR&A deliverables. - Support strategy and portfolio reporting suite in response to new strategies, investor needs, and industry trends. Qualifications: - 5+ years of relevant experience in financial data analysis, credit, valuation skills, or similar roles. - Solid understanding of financial statements, IFRS provisions, and critical covenants. - Hands-on experience with SQL, Python, and Excel for data automation and reconciliation workflows. - Experience building dashboards and data visualizations using reporting platforms. - Availability to work during U.S. PST and India IST working hours. Education: - Bachelor's degree required, preferably in Finance/Accounting; CFA/CA preferred. Personal Attributes: - Self-starter with the ability to operate independently and collaboratively. - Strong interpersonal and communication skills. - Natural problem solver with attention to detail and organizational skills. - Passion for improving systems and processes. - Strong integrity and professionalism. Oaktree is an equal opportunity employer and is committed to diversity and inclusion in the workplace. As a Senior Associate of Investment Data and Reporting at Oaktree, your role will be crucial in overseeing the curation of deal data throughout the investment life cycle, with a focus on credit instruments and markets. You will work closely with deal teams, administrative agents, and middle and back-office teams to ensure accurate and standardized data is captured for internal systems and reporting tools. Your responsibilities will include: - Data Validation and Exception Management: - Spread borrower financials and validate using automation tools. - Prepare monitoring outputs, track valuations, and provide sector-specific KPIs and commentary. - Analyze covenant terms to extract and standardize relevant data. - Streamline data capture for portfolio monitoring, loan administration, valuation, and reporting. - Technology-enabled Reporting: - Utilize Python, SQL, and data visualization tools to manage and manipulate large datasets. - Create standardized reports or dashboards to support decision-making processes. - Partnership & Innovation: - Collaborate with various organizational partners to ensure robust data production and advancement of RR&A deliverables. - Support strategy and portfolio reporting suite in response to new strategies, investor needs, and industry trends. Qualifications: - 5+ years of relevant experience in financial data analysis, credit, valuation skills, or similar roles. - Solid understanding of financial statements, IFRS provisions, and critical covenants. - Hands-on experience with SQL, Python, and Excel for data automation and reconciliation workflows. - Experience building dashboards and data visualizations using reporting platforms. - Availability to work during U.S. PST and India IST working hours. Education: - Bachelor's degree required, preferably in Finance/Accounting; CFA/CA preferred. Personal Attributes: - Self-starter with the ability to operate independently and collaboratively. - Strong interpersonal and communication skills. - Natural problem solver with attention to detail and organizational skills. - Passion for improving systems and processes. - Strong integrity and professionalism. Oaktree is an equal opportunity employer and is committed to diversity and inclusion in the workplace.

As a Senior Analyst - Data Engineering at EY-Strategy and Transactions, you will play a crucial role in supporting cloud and on-prem platform analytics and data engineering projects initiated across engagement teams. Your main responsibilities will involve conceptualizing, designing, developing, deploying, and maintaining complex technology solutions to help EY solve business problems for clients. You will work closely with technical architects, product and business subject matter experts, back-end developers, and other solution architects. **Key Responsibilities:** - Evaluate and select data warehousing tools for business intelligence, data population, data management, metadata management, and warehouse administration for both on-prem and cloud-based engagements - Design, develop, and test in ETL tool environment - Provide technical leadership to a team of data warehouse and business intelligence developers - Coordinate with other technology users to design and implement matters of data governance, data harvesting, cloud implementation strategy, privacy, and security - Adhere to ETL/Data Warehouse development Best Practices - Responsible for Data orchestration, ingestion, ETL, and reporting architecture for both on-prem and cloud - Assist the team with performance tuning for ETL and database processes **Qualifications Required:** - Minimum of 6 years of total experience with 3+ years in Data warehousing/ Business Intelligence field - Strong hands-on experience with creation and implementation of data warehouses on client engagements - Knowledge of data architecture for staging and reporting schemas, data models, and cutover strategies - Experience in Azure database offerings and various Azure services - Strong in PySpark, SparkSQL - Hands-on experience using business intelligence reporting tools - Experience with the software development lifecycle (SDLC) and principles of product development - Bachelors or equivalent degree in computer science, or related field required - Fact-driven and analytically minded with excellent attention to details - Relevant work experience of minimum 6 to 8 years in a big 4 or technology/consulting set up At EY, you will have the opportunity to work on inspiring and meaningful projects while receiving support, coaching, and feedback from engaging colleagues. You will have the freedom and flexibility to handle your role in a way that suits you best, with opportunities to develop new skills and progress your career. EY is dedicated to helping clients create long-term value and build trust in the capital markets, all while working towards building a better working world.,

As a Principal SW Engineering Manager at Microsoft, you will have the opportunity to lead a team of highly motivated software developers in building highly scalable data platforms to empower Microsoft's customer, seller, and partner ecosystem. Your role will involve collaborating with a diverse engineering team to enable end-to-end business scenarios using cutting-edge technologies and solve challenging problems for large-scale 24x7 business SaaS applications. If you are passionate about technology, customer needs, and building innovative solutions, this role is for you. **Key Responsibilities:** - Build and lead a world-class data engineering team. - Champion data-driven decisions for feature identification, prioritization, and delivery. - Manage multiple projects, timelines, customer interactions, and feature tradeoffs. - Deliver on an ambitious product and services roadmap, including building new services on top of vast amounts of collected data. - Design and architect internet-scale and reliable services. - Leverage machine learning models knowledge to select appropriate solutions for business objectives. - Communicate effectively and build relationships with partner teams and stakeholders. - Help shape long-term architecture and technology choices across the full client and services stack. - Understand the talent needs of the team and assist in recruiting new talent. - Mentor and grow other engineers to enhance efficiency and productivity. - Experiment with and recommend new technologies to simplify or improve the tech stack. - Work towards building an inclusive working environment. **Qualifications:** **Basic Qualifications:** - Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. - 12+ years of experience in building high-scale enterprise Business Intelligence and data engineering solutions. - 3+ years of management experience leading a high-performance engineering team. - Proficient in designing and developing distributed systems on a cloud platform. - Experience with a variety of data stores, including data ETL/ELT, data warehouses, RDBMS, in-memory caches, and document databases. - Experience using ML, anomaly detection, predictive analysis, and exploratory data analysis. - Strong understanding of the value of Data and data exploration. - Strong communication skills and proficiency with executive communications. - Demonstrated ability to effectively lead and operate in a cross-functional global organization. **Preferred Qualifications:** - Prior experience as an engineering site leader is a strong plus. - Proven success in recruiting and scaling engineering organizations effectively. - Demonstrated ability to provide technical leadership to teams, managing large-scale data engineering projects. - Hands-on experience working with large data sets using tools such as SQL, Databricks, PySparkSQL, Synapse, Azure Data Factory, or similar technologies. - Expertise in AI, Machine Learning, Business Intelligence, or data visualization tools like Power BI is highly beneficial. If you are excited about collaborating with a diverse engineering team, using the latest technologies to drive AI transformation, and leading the development of innovative data platforms, we invite you to join us at Microsoft.,

As a Quality Assurance Engineer for data testing, your role will involve designing, developing, and executing comprehensive test plans, test cases, and test scripts for ETL/ELT data pipelines. You will be responsible for validating large volumes of data in data warehouses, with a particular focus on Snowflake environments. Your tasks will include performing end-to-end data validation, source-to-target data mapping, and regression testing. Additionally, you will need to identify, report, and track data quality issues, collaborating closely with data engineers and analysts to ensure timely resolution. Automation of data quality tests using SQL and QA automation frameworks will also be a part of your responsibilities. In case of issues in ETL processes, you will conduct root cause analysis and provide actionable recommendations. Your involvement in Agile development processes, such as sprint planning, stand-ups, and retrospectives, will be crucial. You will provide QA sign-off for data pipeline releases and ensure that delivery meets functional and non-functional requirements. Qualifications Required: - Minimum 5 years of experience in Quality Assurance with a focus on data testing. - Strong experience in ETL/ELT testing and data warehousing concepts. - Proficiency in Snowflake and SQL for data validation and analysis. - Experience with test management tools and defect tracking systems. - Strong analytical and problem-solving skills. - Excellent communication and collaboration abilities.,