Top Data Engineer Jobs in Delhi

This role involves leading SAP data migration projects, developing ETL processes, ensuring data quality, and collaborating with cross-functional teams to optimize data integration and management strategies in SAP environments.

Design, build, and optimize scalable ELT/ETL pipelines on Azure using ADF and Databricks, integrate data into Snowflake, implement Data Vault 2.0 modelling, ensure data quality and performance, and collaborate with stakeholders and analytics teams to maintain production workflows.

Design, build, and maintain scalable batch and real-time data pipelines on Azure using Kafka, Spark, Databricks and ADF. Optimize Snowflake models and SQL, process structured and semi-structured data, ensure data quality, performance, and collaborate with cross-functional teams.

The Senior Data Engineer will design, build, and maintain scalable data processing systems, optimizing data pipelines, and collaborating on data architecture.

Design and optimize prompts for AI systems, evaluate model performance, collaborate with teams on machine learning strategies, and document best practices.

The role involves designing and building enterprise-scale data platform services, managing multi-tenant architectures, mentoring engineers, and driving technical initiatives in a remote environment.

As a Senior Developer, you will design and support application and data integration processes using Oracle and Dell Boomi, lead implementation projects, and collaborate on data migration requirements.

As a QA Automation Engineer, you'll design and maintain automated test frameworks for data workflows, validate data quality, and ensure reliability across ETL/ELT pipelines while collaborating with data teams.

The Senior Data Engineer will lead data architecture, mentor engineers, implement data solutions, and ensure data governance while collaborating across teams.

The Principal Developer will lead the design, development, and maintenance of application and data integrations using various tools, ensuring high-quality solutions and collaboration across teams.

Provide application support and IT operations for AI and data platforms, deploy and monitor GenAI and machine learning models, troubleshoot production issues, collaborate with data scientists, and ensure system reliability and performance.