Top Data Engineer Jobs in Delhi

The Data Engineer will design, develop, and maintain ETL/ELT data pipelines, leveraging PySpark and Databricks to process large datasets, ensuring data quality, reliability, and performance optimization.

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.

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.

As a Data Engineer, you will analyze and enrich structured and unstructured data, enhance data quality, and develop insights for financial strategies.

As a Data Engineer, you will enhance data pipelines, support ML workflows, and improve cloud infrastructure on Azure and AWS, collaborating with Scientists and Engineers to turn data into actionable insights.

Principal Data Engineer responsible for building big-data solutions using PySpark and Databricks, writing and optimizing SQL, developing Python pipelines, and working with Hadoop/Hive, Git, Airflow/Dagster, and Azure.

The role involves data modeling, troubleshooting complex issues, optimizing storage architectures and mentoring junior engineers while working with GCP and Python.

The Data Engineer will design, build, and maintain ETL pipelines and data products, utilizing big data technologies and ensuring efficient data architecture. Responsibilities include troubleshooting complex issues, developing scalable solutions, and managing databases and data security compliance.

The Data Engineer role involves designing and maintaining ETL pipelines, optimizing data storage solutions, collaborating with teams, and ensuring data accuracy and integrity.

Build and maintain scalable Azure and Databricks ETL/ELT pipelines using SQL and Python/PySpark. Design cloud-native data lakes, ingest/process data with ADF/ADLS, optimize data models, monitor pipeline health, troubleshoot failures, and collaborate with architects, QA, DevOps, and business teams.

Build and maintain scalable Azure cloud data platforms and ETL/ELT pipelines using Databricks, Synapse, ADF, ADLS. Develop SQL and Python/PySpark transformations, monitor pipeline health, troubleshoot failures, and collaborate with architects, QA, DevOps, and business stakeholders.

The Azure Data Engineer will design and maintain data pipelines, optimize data workflows, and ensure system performance, leveraging Azure technologies.

The Data Engineer will build and optimize data pipelines, using SQL and Python while working collaboratively to support business analytics and AI initiatives.

The Associate Data Engineer will assist in building and maintaining data pipelines, writing SQL queries, and ensuring data quality using tools like Snowflake and Matillion.

Design and implement scalable enterprise data architectures (data lakes, warehouses, data fabric, MDM). Build and optimize data pipelines, define governance, quality, lineage, and security standards. Enable AI/ML initiatives through data engineering, collaborate with stakeholders, and create data strategy and platform roadmaps.

The Data Engineer will translate analytical requirements into scalable data products, handle data modeling in Snowflake using dbt, manage data pipelines with Airflow, ensure data quality, and collaborate with cross-functional teams.

The Senior Associate Data Engineer develops structured datasets for analysis, manages ETL processes, and designs data models to support business analytics and reporting.

Design, build, and operationalize AI-enabled data pipelines and production-grade AI applications using Python and Snowflake. Prepare and transform large datasets, develop features and embeddings, support deployment and monitoring of ML/LLM models, optimize Snowflake for AI workloads, and collaborate with data science and engineering teams to deliver scalable APIs and RAG-enabled data workflows.

The role involves designing and building data infrastructure, developing ETL/ELT applications, collaborating with teams, and improving engineering processes for analytics and AI capabilities.

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.

Develop and support Azure-based ETL/ELT data pipelines and analytics solutions. Build and maintain database objects in Azure SQL, Microsoft Fabric, and Snowflake. Monitor and troubleshoot production pipelines, support analytics requests from business users, and maintain technical documentation and version-control standards.

Design, develop, and support Azure-based data pipelines and analytics solutions. Build and maintain database objects in Azure SQL, Fabric, and Snowflake, monitor production pipelines, troubleshoot data issues, support business analytics requests, and maintain technical documentation and version control.

Build, support, and monitor Azure-based data pipelines and analytics solutions. Develop database objects in Azure SQL, Microsoft Fabric, and Snowflake, troubleshoot production data flows, support business analytics requests, maintain technical documentation, and follow development/version-control standards.

We are looking for a Data Engineer with skills in Python, SQL, and Azure technologies to develop Big Data applications. Responsibilities include working with Spark and Docker to handle large scale data processing and analytics.

The Azure Data Engineer will build data pipelines and dataflows, implement security modules, and work with Azure services while supporting business requirements and data analysis.