Top Data Engineer Jobs in Delhi

Design, build, and operate scalable ETL/ELT pipelines using PySpark and AWS data services. Orchestrate workflows with Apache Airflow, implement AWS Glue jobs and Data Catalog, manage Lake Formation permissions, publish datasets for BI, and deliver QuickSight visualizations while ensuring data quality and performance.

No role-specific responsibilities provided in the posting. Typically, a Unit Manager - Data Governance leads the data governance function: defining and enforcing data policies, managing data quality and metadata, coordinating stakeholders, ensuring regulatory compliance, and supervising a team to implement governance processes.

Design, develop, implement and maintain Big Data solutions for Disability & Absence products. Build batch, speed, and serving layers using Spark, Hive, NoSQL, SOLR and Kafka; optimize Hadoop jobs; automate with Shell/Python; support deployments, CI/CD, runbooks, and cross-team collaboration.

As a Data Engineer, you will work with GCP technologies, managing big data, utilizing ETL/ELT processes, and collaborating across teams while advancing in your career.

The Google Cloud Data Engineer will design and implement data pipelines using Google Cloud technologies and collaborate with analysts to ensure data quality and governance.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

As a Data Engineer, you will build data pipelines, design data models, and deploy Data Ops, collaborating with multiple teams to enhance product offerings.

As a Senior Software Engineer on the Data Platform team at Coinbase, you will design, build, and operate data services, ensuring data accessibility and security while empowering users to manage their data pipelines.

The role involves designing and maintaining ETL pipelines, ensuring data quality and compliance, leading teams, and collaborating with various business partners.

The Senior Data Engineer will build ETL/ELT processes, develop reusable frameworks, optimize performance, and collaborate with teams to deliver data solutions.

Responsible for implementing business logic in data warehouses, designing ETL pipelines, optimizing data processes, and collaborating with stakeholders for data-driven improvements.

The Data Engineer will build and maintain Azure-based data platforms, develop data pipelines, implement Microsoft Fabric, integrate Power BI, and ensure data security and governance.

The Data Engineer will lead the creation and maintenance of the company's data infrastructure, build reporting capabilities, and develop data-driven automation pipelines.

The Data Engineer role involves designing and maintaining data pipelines, ensuring data quality, integrating data sources, and collaborating across teams to enhance BitGo's data infrastructure.

As a Data Engineer, you'll develop data pipelines, automate processes, and collaborate with teams to enhance data management and analytics for national security. You'll analyze raw data, manage data platforms, and engage with clients.

The Python Data Engineer is responsible for developing Python applications, designing ETL pipelines, integrating APIs, and managing data solutions to enable data-driven decision making.

Maintain and monitor web scraping configurations, ingest and transform scraped data into the data lake, detect and resolve pipeline issues, produce stakeholder reports, and build scalable ETL pipelines and data architectures to support analytics.

Design, develop, and maintain Big Data solutions for Disability & Absence products. Collaborate with teams to improve existing solutions and create automation scripts.

As a Data Engineer at InfyStrat, you'll design and maintain data architecture, ensuring data accessibility and reliability while developing data pipelines. You'll collaborate with teams to create scalable data solutions for business intelligence.

The Data Engineer will design, build, and maintain scalable data pipelines using Databricks, integrating data into systems and ensuring data quality and performance while collaborating with stakeholders.

The Data Engineer will design, build, and maintain data pipelines for Data Warehouses, utilizing AWS, GCP, and SQL, while ensuring data quality and implementing CI/CD best practices.

Design and build AI data architecture and APIs with Python/Django; manage SQL, MongoDB and Pinecone vector databases; integrate and optimize AI models, context/prompt builders; collaborate with leadership and engineers; research AI/data engineering advancements.

The Big Data Engineer will design and develop scalable data solutions, build data pipelines, ensure data quality, and collaborate across teams.

Develop and maintain scalable data pipelines in Azure and Microsoft Fabric, optimize data workflows, and apply scientific algorithms to climate model data.

The Data Warehouse Operations Senior Engineer will monitor, maintain, and optimize the enterprise data warehouse, ensuring stability and performance of ETL, reporting, and cloud infrastructure. Responsibilities include troubleshooting, compliance, incident management, and system performance monitoring.