382 Dbt Jobs

Role Overview: This job is part of the Database Engineering job function, where you will be responsible for the upkeep of databases across several company platforms and computing environments. Key Responsibilities: - Design, develop, and maintain robust data warehouse solutions to support business intelligence and analytics needs - Design, implement, and manage metadata frameworks to ensure data consistency and quality - Develop and maintain reference data and dimensional data models to support various business processes - Design and implement ETL (Extract Transform Load) processes using tools like SnapLogic or Informatica to integrate data from multiple sources - Utilize Python for data manipulation, automation, and integration tasks - Optimize the performance of data systems and processes - Implement transformations in DBT (Data Build Tool) to streamline data workflows - Collaborate with cross-functional teams to develop and maintain reporting tools and dashboards - Implement data governance practices to ensure data integrity, security, and compliance - Stay updated with the latest advancements in Generative AI and explore opportunities to integrate AI solutions into data engineering processes Qualifications Required: - Bachelor's degree in Computer Science, Information Technology, or a related field - 7 to 10 years of relevant experience in working with data platforms - Strong knowledge of data warehouse concepts, metadata frameworks, reference data, and dimensional data modeling - Proficiency in ETL processes and tools like SnapLogic or Informatica - Advanced skills in Python programming - Experience with databases such as SQL Server, PostgreSQL, and Snowflake - Advanced SQL knowledge - Experience with reporting tools such as Tableau, Power BI, or similar - Understanding of data governance principles and best practices - Knowledge of Generative AI and its applications is a plus - Experience with DBT (Data Build Tool) for data transformations - Ability to optimize the performance of data systems and processes - Excellent problem-solving skills and attention to detail - Strong communication and collaboration skills (No additional details of the company were present in the JD),

As a highly experienced Data Modeler/ETL Architect with expertise in data modeling, ETL design, and DBT frameworks, your role will involve designing, implementing, and optimizing scalable data models, pipelines, and data architecture to support enterprise-level analytics and data warehouse solutions. - Design and maintain conceptual, logical, and physical data models for enterprise data platforms. - Lead the architecture, development, and optimization of ETL/ELT workflows using DBT, SQL, and modern data integration tools. - Define and implement data modeling standards, best practices, and governance frameworks. - Collaborate with data engineers, analysts, and business stakeholders to translate requirements into robust data solutions. - Architect data pipelines ensuring data quality, integrity, and consistency across multiple systems. - Optimize data models for performance, scalability, and reusability in analytical workloads (Snowflake, Redshift, BigQuery, etc.). - Oversee data lineage, metadata management, and documentation for transparency and maintainability. - Provide technical leadership and mentorship to data engineers and analysts in data modeling and DBT development. - Participate in data architecture reviews, performance tuning, and troubleshooting. Qualifications: - 10+ years of experience in data engineering, data modeling, or data architecture. - Expertise in ETL/ELT design and architecture using modern data integration platforms. - Proficiency in SQL and experience with cloud data warehouses (e.g., Snowflake, Redshift, BigQuery, Azure Synapse). - Hands-on experience with data modeling techniques (3NF, star schema, data vault, dimensional modeling). - Solid understanding of data governance, data lineage, and data quality frameworks. - Experience in cloud platforms (AWS, Azure, or GCP). - Understanding of business intelligence (BI) and analytics tools such as Looker, Power BI, or Tableau. - Familiarity with version control (Git), CI/CD for data pipelines, and agile development practices. - Strong problem-solving, analytical, and communication skills. Please note that the company details were not provided in the job description.,

Job Description You are looking for a Senior DBT Engineer with 8-12 years of experience. Role Overview As a Senior Data Engineer with significant ELT experience, you will focus on building scalable, efficient, and well-governed DBT data models on modern cloud platforms. Key Responsibilities - Design and build DBT models (staging, intermediate, marts) following best practices. - Develop reusable macros, tests, and transformations to support analytics and reporting. - Optimize SQL queries, data warehouse performance, and ELT workflows.,

As a Data & Machine Learning (ML) Engineer at VIWELL, you will be instrumental in enhancing VIWELL's personalization and intelligent recommendation systems. Your role will involve collaborating with various teams to deliver high-quality events, features, eligibility rules, ranking logic, and safe GPT rewrites that aim to enhance user engagement and personalization within VIWELL's ecosystem. Your efforts will directly contribute to VIWELL's mission of scaling to millions of users through intelligent, privacy-preserving, and high-performance data and ML systems. **Key Responsibilities:** - Define event schemas and data contracts in collaboration with Product and Analytics for high-quality tracking and feature availability. - Engineer and maintain data features in Databricks with robust quality checks, lineage documentation, and automated orchestration. - Design and implement eligibility rules and ranking logic for safe personalization and recommendations. - Build guardrails and validation systems like blocklists, allowlists, rewrite validators, and pseudonymization frameworks for safe GPT-assisted rewrites. - Design A/B experiments, exposure logging, and statistical frameworks to support iterative product improvements. - Integrate ML and personalization systems with backend APIs for optimized response times below 300 milliseconds. - Collaborate with cross-functional teams to ensure clarity, alignment, and seamless execution of data and ML solutions. - Stay updated on evolving AI safety principles, data quality standards, and best practices in ML engineering. - Continuously enhance feature pipelines, data freshness, ranking performance, and validation accuracy. **Qualifications & Experience:** - Bachelor's or master's degree in computer science, Engineering, Data Science, Machine Learning, or related technical field. - 5-7 years of experience in data engineering, machine learning engineering, or applied ML roles. - Hands-on experience with Python, SQL, Databricks, MLflow, and modern data engineering tooling. - Experience with dbt or similar transformation frameworks and strong understanding of data contracts and quality checks. - Proven experience in designing ML ranking systems, eligibility rules, or recommendation logic with a safety-first mindset. - Familiarity with A/B testing, statistical experimentation, and product analytics. - Exposure to privacy-by-design, pseudonymization, and security best practices in data workflows. - Ability to thrive in a fast-paced environment and manage multiple concurrent priorities. - Excellent communication, problem-solving, and stakeholder management skills. **What We Offer:** - Competitive salary package based on experience. - Opportunity to build impactful, safety-focused AI and ML systems used by millions of users. - Collaborative, innovation-driven, and mission-led work culture. - Career growth opportunities within the fast-evolving AI, wellness, and technology landscape. If you meet the criteria and are ready to contribute to a purpose-driven company, send your CV to career@viwell.com and be part of transforming well-being across the region!,

As a skilled and detail-oriented Snowflake & DBT Developer with 6 to 9 years of experience in data engineering and transformation, your role will involve the following responsibilities: - Design, develop, and maintain data pipelines using Snowflake and DBT. - Write efficient and reusable SQL and Jinja templates for data transformations. - Collaborate with data analysts, engineers, and business stakeholders to understand data requirements. - Optimize data models and queries for performance and scalability. - Implement data quality checks and validation processes. - Use Python for scripting, automation, and integration tasks as needed. - Participate in code reviews, testing, and deployment processes. Qualifications required for this role include proficiency in Snowflake, DBT (with Jinja and SQL), and a working knowledge of Python.,

As an experienced ETL developer with 4+ years of experience, you should have proficiency in DBT and Matillion ETL for Snowflake. Your expertise in SQL query optimization, data modeling, and GitHub workflows will be crucial for this role. Additionally, having certifications in Snowflake and Matillion would be a plus. - Role Overview: You will be responsible for ETL development with a focus on DBT and Matillion ETL for Snowflake. Your role will involve optimizing SQL queries, data modeling, and utilizing GitHub workflows to streamline processes. - Key Responsibilities: - Develop ETL processes using DBT and Matillion ETL for Snowflake. - Optimize SQL queries to improve performance and efficiency. - Create and maintain data models to support business requirements. - Collaborate with team members to implement best practices for ETL development. - Stay updated on industry trends and technologies related to ETL and data warehousing. - Qualifications Required: - Minimum 4 years of experience in ETL development. - Proficiency in DBT and Matillion ETL for Snowflake. - Expertise in SQL query optimization, data modeling, and GitHub workflows. - Certifications in Snowflake and Matillion would be a plus.,

As an experienced DBT professional at our company, you will be responsible for designing, developing, and technical architecture of data pipelines in a big data environment. Your expertise in PL/SQL, Snowflake SQL, Unix, Python, and Talend will be crucial in ensuring data quality and performance scaling. Candidates with PROD support experience will be preferred. Key Responsibilities: - Write and optimize PL/SQL queries, procedures, and JOINs - Develop SQL queries against Snowflake and scripts in Unix, Python for ETL operations - Utilize Snowflake utilities such as SnowSQL, SnowPipe, Python, Tasks, and more - Perform data analysis, troubleshoot issues, and provide technical support - Maintain data warehouse and ETL processes to ensure data quality and integrity - Demonstrate complex problem-solving skills and continuous improvement mindset - Collaborate effectively within a global team environment - Familiarity with Agile delivery process Qualifications Required: - Hands-on experience with Talend and Snowflake - Desirable to have Talend/Snowflake Certification - Excellent SQL coding, communication, and documentation skills - Analytical, creative, and self-motivated mindset,

As a Data Engineer II at Ethoca, a Mastercard Company, located in Pune, India, you will play a crucial role in driving data enablement and exploring big data solutions within the technology landscape. Your expertise in cutting-edge software development, full stack development, cloud technologies, and data lake experience will be key in working with massive data volumes. Here's an overview of your role: Key Responsibilities: - Design, develop, and optimize batch and real-time data pipelines using Snowflake, Snowpark, Python, and PySpark. - Build data transformation workflows using dbt, focusing on Test-Driven Development (TDD) and modular design. - Implement and manage CI/CD pipelines using GitLab and Jenkins for automated testing, deployment, and monitoring of data workflows. - Deploy and manage Snowflake objects using Schema Change to ensure controlled, auditable, and repeatable releases across environments. - Administer and optimize the Snowflake platform, including performance tuning, access management, cost control, and platform scalability. - Drive DataOps practices by integrating testing, monitoring, versioning, and collaboration throughout the data pipeline lifecycle. - Develop scalable and reusable data models for business analytics and dashboarding in Power BI. - Support real-time data streaming pipelines using technologies like Kafka and Spark Structured Streaming. - Establish data observability practices to monitor data quality, freshness, lineage, and anomaly detection. - Plan and execute deployments, migrations, and upgrades across data platforms and pipelines with minimal service impacts. - Collaborate with stakeholders to understand data requirements and deliver reliable data solutions. - Document pipeline architecture, processes, and standards to ensure consistency and transparency within the team. - Utilize problem-solving and analytical skills to troubleshoot complex data and system issues. - Communicate effectively with technical and non-technical teams. Required Qualifications: - Bachelor's degree in Computer Science/Engineering or related field. - 4-6 years of professional experience in software development/data engineering. - Deep hands-on experience with Snowflake/Data Bricks, Snowpark, Python, and PySpark. - Familiarity with Schema Change, dbt, Java JDK 8, Spring & Springboot framework. - Proficiency in CI/CD tooling (GitLab, Jenkins), cloud-based databases (AWS, Azure, GCP), Power BI, and SQL development. - Experience in real-time data processing, building data observability tools, and executing deployments with minimal disruption. - Strong communication, collaboration, and analytical skills. By joining Ethoca, a Mastercard Company, you will be part of a team committed to building a sustainable world and unlocking priceless possibilities for all. Your contributions as a Data Engineer II will be instrumental in shaping the future of the high growth fintech marketplace.,

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.,

You will be responsible for: - Designing, developing, and maintaining data pipelines and ETL/ELT workflows using GCP-native tools and services. - Building and optimizing data warehouses using Snowflake. - Writing complex and efficient SQL queries for data transformation, analysis, and reporting. - Collaborating with analysts, data scientists, and business stakeholders to understand data needs and deliver reliable solutions. - Implementing data governance, security, and monitoring best practices across GCP projects. - Tuning queries and optimizing performance of large-scale datasets. - Automating workflows using Cloud Composer (Airflow) or similar orchestration tools. Your Skills & Qualifications should include: - 3+ years of experience in a data engineering or data platform role. - Strong hands-on experience with Snowflake data warehousing. - Expert-level skills in SQL, able to write optimized, scalable, and complex queries. - Experience with data modeling (star/snowflake schema), partitioning, clustering, and performance tuning in a data warehouse. - Familiarity with modern ELT tools such as dbt, Fivetran, or Cloud Data Fusion. - Experience in Python or similar scripting language for data engineering tasks. - Understanding of data governance, privacy, and Google Cloud Platform services, especially BigQuery, Cloud Storage, Dataflow, Pub/Sub, Composer.,

As a Senior Data Engineer specializing in Snowflake and DBT, your role will involve designing, developing, and optimizing data pipelines using Airflow, Python, and DBT. You will be responsible for building and maintaining data models and data marts in Snowflake, implementing best practices in data transformation, testing, and documentation using DBT, and ensuring data quality, governance, and lineage across data pipelines. Additionally, you will collaborate with data analysts, scientists, and business stakeholders to understand data needs, optimize query performance and data storage in Snowflake, monitor and troubleshoot data pipeline issues proactively, and automate workflows and schedule tasks using Apache Airflow. Key Responsibilities: - Design, develop, and optimize data pipelines using Airflow, Python, and DBT. - Build and maintain data models and data marts in Snowflake. - Implement best practices in data transformation, testing, and documentation using DBT. - Collaborate with data analysts, scientists, and business stakeholders to understand data needs. - Ensure data quality, governance, and lineage across data pipelines. - Optimize query performance and data storage in Snowflake. - Monitor and troubleshoot data pipeline issues proactively. - Automate workflows and schedule tasks using Apache Airflow. Required Skills & Experience: - 4+ years of experience in data engineering or analytics engineering roles. - Strong expertise in Snowflake (SQL, data warehousing concepts, performance tuning). - Hands-on experience with DBT for data transformation and modeling. - Proficiency in Python for scripting and data manipulation. - Experience with Apache Airflow for workflow orchestration. - Solid understanding of ETL/ELT design principles and data architecture. - Knowledge of CI/CD for data pipelines is a plus. - Strong problem-solving skills and attention to detail. - Excellent communication and collaboration skills. As a Senior Data Engineer specializing in Snowflake and DBT, your role will involve designing, developing, and optimizing data pipelines using Airflow, Python, and DBT. You will be responsible for building and maintaining data models and data marts in Snowflake, implementing best practices in data transformation, testing, and documentation using DBT, and ensuring data quality, governance, and lineage across data pipelines. Additionally, you will collaborate with data analysts, scientists, and business stakeholders to understand data needs, optimize query performance and data storage in Snowflake, monitor and troubleshoot data pipeline issues proactively, and automate workflows and schedule tasks using Apache Airflow. Key Responsibilities: - Design, develop, and optimize data pipelines using Airflow, Python, and DBT. - Build and maintain data models and data marts in Snowflake. - Implement best practices in data transformation, testing, and documentation using DBT. - Collaborate with data analysts, scientists, and business stakeholders to understand data needs. - Ensure data quality, governance, and lineage across data pipelines. - Optimize query performance and data storage in Snowflake. - Monitor and troubleshoot data pipeline issues proactively. - Automate workflows and schedule tasks using Apache Airflow. Required Skills & Experience: - 4+ years of experience in data engineering or analytics engineering roles. - Strong expertise in Snowflake (SQL, data warehousing concepts, performance tuning). - Hands-on experience with DBT for data transformation and modeling. - Proficiency in Python for scripting and data manipulation. - Experience with Apache Airflow for workflow orchestration. - Solid understanding of ETL/ELT design principles and data architecture. - Knowledge of CI/CD for data pipelines is a plus. - Strong problem-solving skills and attention to detail. - Excellent communication and collaboration skills.

As a Snowflake + DBT Developer at our company, you will be an integral part of the Technology Team, focusing on data pipeline migration, modeling, and orchestration using modern data stack technologies like Snowflake, DBT, Databricks, and Airflow. Your role will involve migrating existing pipelines from Databricks to Snowflake, building scalable workflows, and ensuring seamless data integration across environments. **Key Responsibilities:** - Analyze and understand existing data pipelines built using Databricks (PySpark/Spark). - Re-architect and rebuild pipelines for Snowflake using SQL-based transformations and DBT models. - Develop using Snowflake-native features such as Snowpipe, Streams/Tasks, Materialized Views, and more. - Build and manage modular DBT models, macros, and materializations. - Design, build, and manage Airflow DAGs for end-to-end orchestration. - Create and manage automated deployment pipelines using GitHub Actions, Azure DevOps, or similar. - Implement proactive monitoring, logging, and alerting mechanisms for data pipelines. **Technical Requirements:** - 4+ years of experience in data engineering with expertise in Snowflake and DBT. - Strong understanding of Snowflake features such as RBAC, Data Sharing, Database Replication, and more. - Proficiency in SQL development, data modeling, and performance tuning in Snowflake. - Experience with orchestration tools like Airflow and containerized deployments using Docker. - Familiarity with CI/CD pipelines, code versioning, and deployment automation. - Knowledge of data governance, security controls, and masking techniques. In this role, you will be expected to have excellent analytical thinking, communication skills, and the ability to work both independently and collaboratively across teams. Your proactive nature and willingness to mentor peers will be valuable assets in contributing to process improvement and documentation.,

As a Data Engineer - DBT at NTT DATA in Bangalore, Karntaka (IN-KA), India, your main responsibilities will involve: - Strong experience working in projects in DBT - Migration of SAS code to DBT code - Analyzing data models and deriving logical conclusions - Processes modeling - Hands-on development and monitoring of the Azure cloud Platform and various associated components for data ingestion, transformation, and processing - Diagnosing, isolating, and resolving complex problems pertaining to data infrastructure - Designing and writing programs according to functional and non-functional requirements - Developing and maintaining technical documentation - Following established configuration/change control processes Minimum Skills Required: - University level education or equivalent - 2+ years of experience working as a Data Engineer - Knowledge of design patterns - Ability to write complex SQL queries - Good understanding of distributed computation - DBT and GIT proficiency - Experience with Azure cloud and Databricks Nice to have: - Python proficiency - 1+ Experience in functional programming (preferably Scala) - 1+ years of experience in Apache Spark 2.0 - Experience in R programming - Experience with Hadoop technologies (i.e. Sqoop, Hive, Flume, etc.) - Continuous Integration / Continuous Deployment (Azure DevOps) - Experience in data exploration using notebooks (Databricks notebooks) - Experience in the automation of regular tasks (e.g., data refreshes) using bash and Python scripting NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune Global 100. Committed to accelerating client success and positively impacting society through responsible innovation, NTT DATA is one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers, and application services. Their consulting and industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, NTT DATA has experts in more than 50 countries and offers clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is part of NTT Group, which invests over $3 billion each year in R&D.,

As a Data Engineer at Coforge Ltd., you will play a crucial role in developing robust and scalable data pipelines, implementing efficient data models, and ensuring the quality and integrity of data assets. Your expertise in Snowflake and DBT will be essential in building and optimizing our modern data warehouse. Key Responsibilities: - Build efficient and scalable data pipelines to extract, transform, and load data from various sources into the data storage systems. This includes integrating different data formats, performing data cleansing and transformation, and ensuring data quality and consistency. - Design and implement data models to support business requirements and analytical needs. Define data schemas, data structures, and relationships between different data entities. - Optimize data models for performance, scalability, and flexibility. - Collaborate with cross-functional teams, including customers and business analysts, to understand their data requirements and ensure smooth integration and access to data. Work closely with stakeholders to identify data sources and define data integration strategies. - Implement data quality controls, data validation processes, and error handling frameworks to ensure the accuracy, completeness, and consistency of data. Define and enforce data quality standards and best practices across the organization. - Develop and maintain data warehouse and ETL processes to ensure that data is stored and managed effectively. - Develop and maintain data quality standards to ensure that the data is accurate and up-to-date. - Monitor data trends and analyze data to identify patterns and opportunities for improvement. Skills & Abilities Required: - Strong proficiency in Snowflake and DBT. - Experience with data ingestion tools like Fivetran will be an added plus. - Familiarity with AWS cloud services. - Demonstrated ability to deliver project documentation, like design documents, test cases, and scenarios. - Excellent communication and interpersonal skills, with the ability to effectively convey complex technical information to both technical and non-technical stakeholders.,

Role Overview: You will be part of the Consumer Products Center of Expertise team at Bain & Company, collaborating with global Consumer Products Practice leadership, client-facing Bain leadership, and end clients to develop and deliver Bains proprietary CP products and solutions. Your role will involve working with a mix of Directors, Managers, Project Leads, Associates, and Analysts to implement cloud-based end-to-end advanced analytics solutions. You will be expected to contribute to various delivery models within the CP Center of Expertise, global Bain case teams, or other industry CoEs as needed. Key Responsibilities: - Collaborate with data scientists to design, fine-tune, and deploy intelligent agents and chains-based applications using Python, LLMs, NLP, and Generative AI. - Develop front-end interfaces for AI and data science applications using React.js, Angular, Nextjs, Streamlit, and deploy Python-based machine learning models with backend systems via RESTful APIs. - Translate complex business problems into scalable technical solutions, integrating AI capabilities with robust backend and frontend systems. - Assist in designing and implementing scalable data pipelines and ETL workflows using DBT, PySpark, and SQL, supporting analytics and generative AI solutions. - Utilize containerization tools like Docker, version control with Git, and deploy ML-powered applications on cloud platforms such as AWS or Azure. - Contribute to internal AI/ML Ops platforms, create dashboards, visualizations, and presentations to drive business insights using tools like Tableau, PowerBI, Plotly, and Seaborn. Qualifications Required: - Masters degree or higher in Computer Science, Data Science, Engineering, or related fields OR Bachelor's degree with relevant industry experience. - Proven experience in AI/ML, software development, and data engineering. - Solid understanding of LLMs, NLP, Generative AI, chains, agents, and model fine-tuning methodologies. - Proficiency in Python and experience with libraries like Pandas, Numpy, Plotly, and Seaborn. - Frontend development skills using HTML, CSS, JavaScript/TypeScript, and modern frameworks like React.js; familiarity with Streamlit is a plus. - Strong grasp of data engineering concepts, cloud infrastructure (AWS and/or Azure), and deployment best practices. - Familiarity with MLOps/AI Ops tools and workflows, BI tools such as Tableau or PowerBI, and exposure to consulting projects or CP business domain is advantageous. (Note: Additional details about the company were not provided in the job description.),

As a Remote Senior Data Engineer (ETL Data Modeling) for our client in the UK, you will play a crucial role in expanding the external technical platform, meeting customer needs, and promoting technical excellence within the team. **Key Responsibilities:** - Implement ETL/ELT pipelines using Python, Pyspark, and Snowflake's Snow SQL within and outside of a data warehouse. - Assist in the migration from Redshift DWH to Snowflake. - Design, implement, and maintain data warehouse/data lake infrastructure utilizing AWS big data stack, Python, Redshift, Snowflake, Glue/lake formation, EMR/Spark/Scala, etc. - Collaborate with data analysts to enhance value-creating capabilities, including data integrations, transformations, model features, and statistical/machine learning models. - Engage with various teams like Product Managers, Finance, Service Engineering, and Sales to meet their analytics requirements. - Implement data quality and data governance measures, conduct data profiling, and execute data validation procedures. - Uphold data governance practices to ensure data quality, integrity, and security throughout the data lifecycle. - Utilize open-source technologies to construct robust and cost-effective data solutions. - Develop and manage streaming pipelines using technologies like Apache Kafka. **Qualifications Required:** - Minimum 5 years of IT experience with at least 3 years in data Integration, ETL/ELT development, and database design or Data Warehouse design. - Proficiency in distributed systems, streaming systems, and data engineering tools like Kubernetes, Kafka, Airflow, Dagster, etc. - Experience in data transformation, ETL/ELT tools (AWS Glue, DBT, etc.), and ingesting/integrating data from various sources. - Deep knowledge of Python, SQL, relational/non-relational database design, and master data strategies. - Experience in defining, architecting, and deploying data products, including managing them through their lifecycle. - Familiarity with Star and Snowflake dimensional modeling, relational databases, SQL queries, and data warehouses. - Strong SQL proficiency and expertise in at least one programming language (Python, Scala, JS). - Knowledge of data orchestration tools like Apache Airflow and agile methodologies. - Proficiency with version control systems like Bitbucket/Git. - Ability to thrive in a fast-paced startup environment, handle changing requirements, and manage multiple ongoing projects simultaneously. - Excellent verbal and written communication skills. The company offers a dynamic work environment in a rapidly growing organization, international exposure, a flat hierarchy, intellectually stimulating work, and flexible working hours. (Note: Preferred/bonus skills and details about the company's work environment have been omitted as per your request),

As a DBT Engineer at NTT DATA, your primary role will involve translating Informatica mappings, transformations, and business rules into dbt models (SQL) on Snowflake. You will be responsible for designing and implementing staging, core, and mart layers using standard dbt patterns and folder structures. Your duties will also include developing and maintaining dbt tests (schema tests, data tests, custom tests) to ensure data quality and integrity. Additionally, you will implement snapshots, seeds, macros, and reusable components where appropriate. Collaborating with Snowflake developers to ensure physical data structures support dbt models efficiently will be a crucial part of your responsibilities. Key Responsibilities: - Translate Informatica mappings, transformations, and business rules into dbt models (SQL) on Snowflake - Design and implement staging, core, and mart layers using standard dbt patterns and folder structures - Develop and maintain dbt tests (schema tests, data tests, custom tests) to ensure data quality and integrity - Implement snapshots, seeds, macros, and reusable components where appropriate - Collaborate with Snowflake developers to ensure physical data structures support dbt models efficiently - Ensure functional equivalence between legacy Informatica outputs and new dbt outputs - Participate in performance tuning of dbt models and Snowflake queries - Integrate dbt with CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for automated runs and validations - Contribute to documentation of dbt models, data lineage, and business rules - Participate in defect analysis, bug fixes, and enhancements during migration and stabilization phases Qualifications Required: - 13+ years of experience in Data Engineering / ETL / DW, with 3+ years working with dbt (Core or Cloud) - Strong SQL skills, especially on Snowflake or another modern cloud DW - Experience with dbt concepts: models, tests, sources, seeds, snapshots, macros, exposures - Prior experience with Informatica (developer-level understanding of mappings/workflows) is highly desirable - Understanding of CI/CD practices and integrating dbt into automated pipelines - Knowledge of data modeling (dimensional models, SCDs, fact/dimension design) - Experience working in offshore delivery with onshore coordination - Good communication skills and ability to read/understand existing ETL logic and requirements documentation In addition to the job description, NTT DATA is a $30 billion business and technology services leader, committed to accelerating client success through responsible innovation. With capabilities in enterprise-scale AI, cloud, security, connectivity, data centers, and application services, NTT DATA is dedicated to helping organizations and society move confidently into the digital future. As a Global Top Employer, NTT DATA operates in more than 50 countries, offering clients access to a robust ecosystem of innovation centers and established and start-up partners. NTT DATA is part of the NTT Group, which invests over $3 billion each year in R&D.,

As a Data Engineer at Birlasoft, you will play a crucial role in designing and developing data transformations and models to ensure efficient data processing and analysis. Your expertise in DBT (Data Build Tool) and Snowflake will be instrumental in supporting data-driven decision-making processes and contributing to the success of our insights teams. Here are the key responsibilities you will be expected to undertake: - Design and develop robust data pipelines using DBT and Snowflake to ensure reliable data processing. - Implement and optimize data ingestion processes for efficient and accurate data flow from various sources. - Collaborate with cross-functional teams to understand data requirements, ensuring data integrity and quality. - Conduct data analysis and profiling to identify and address data quality issues. - Maintain comprehensive documentation of data workflows, models, and ETL processes. - Stay updated with the latest trends and technologies in data engineering, DBT, and Snowflake. Qualifications required for this role include: - Proven experience as a Data Engineer with a focus on data ingestion and ETL processes. - Proficiency in SQL and experience with programming languages such as Python or Java. - Familiarity with cloud platforms and services, with experience on AWS Lambda being a must. - Experience with other ETL tools and technologies is a plus (e.g., Apache Airflow, Talend, Informatica). - Adherence to development best practices, including version control using Git and branching models. - Participation in scrum methodology, including daily stand-ups, sprint planning, and retrospectives. - Effective communication with team members and stakeholders to understand requirements and provide updates. - Ability to take ownership of assigned tasks and work independently to complete them. Join Birlasoft and be a part of a global leader in Cloud, AI, and Digital technologies. Your contributions as a Data Engineer will have a direct impact on enhancing the efficiency and productivity of businesses worldwide.,

Role Overview: As a Data Engineer, your responsibility will be to design, develop, and maintain scalable data pipelines using AWS services and Snowflake. Your primary focus will involve building and managing data transformation workflows using dbt. Collaboration with data analysts, data scientists, and business stakeholders is crucial to ensure the delivery of clean, reliable, and well-documented datasets. Key Responsibilities: - Optimize Snowflake performance through clustering, partitioning, and query tuning. - Implement data quality checks, testing, and documentation within dbt to ensure data accuracy. - Automate data workflows and integrate with CI/CD pipelines. - Ensure data governance, security, and compliance across cloud platforms. Qualifications Required: - Strong experience with Snowflake, including data modeling, performance tuning, and security. - Proficiency in dbt, including models, macros, testing, and documentation. - Solid understanding of AWS services such as S3, Lambda, Glue, and IAM. - Experience with SQL and scripting languages like Python. - Familiarity with version control systems like Git and CI/CD tools.,

Role Overview: As a Data Engineer - DBT at NTT DATA, you will be part of the DBI organization within the Data Scientist & Data Engineering team. Your main responsibilities will involve strong experience in projects involving DBT, particularly focusing on the migration of SAS code to DBT code. You will analyze data models, develop processes, and work hands-on with the Azure cloud platform for data ingestion, transformation, and processing. Additionally, you will be responsible for diagnosing and resolving complex problems related to data infrastructure, designing and writing programs, and maintaining technical documentation. Key Responsibilities: - Work on projects involving DBT, specifically the migration of SAS code to DBT code - Analyze data models and derive logical conclusions - Develop processes modeling - Hands-on development and monitoring of Azure cloud platform for data operations - Diagnose, isolate, and resolve complex problems related to data infrastructure - Design and write programs based on functional and non-functional requirements - Develop and maintain technical documentation - Follow established configuration/change control processes Qualifications Required: - University level education or equivalent - 2+ years of experience working as a Data Engineer - Knowledge of design patterns - Ability to write complex SQL queries - Good understanding of distributed computation - Experience with DBT, GIT, Azure cloud, and Databricks - Nice to have: Python, functional programming experience (preferably Scala), Apache Spark 2.0 experience, R programming, Hadoop technologies knowledge, Continuous Integration / Continuous Deployment (Azure DevOps), data exploration using notebooks, automation of regular tasks using bash and Python scripting About NTT DATA: NTT DATA is a $30+ billion business and technology services leader, serving 75% of the Fortune Global 100. Committed to accelerating client success and positively impacting society through responsible innovation, NTT DATA is a leading AI and digital infrastructure provider. With expertise in enterprise-scale AI, cloud, security, connectivity, data centers, and application services, NTT DATA helps organizations and society transition confidently into the digital future. As a Global Top Employer with experts in more than 50 countries, NTT DATA offers clients access to a robust ecosystem of innovation centers and partners. NTT DATA is part of the NTT Group, which invests over $3 billion annually in R&D.,