Top Data Engineer Jobs in Gurgaon

As a Data Engineer, you will create data pipelines, ensure data quality, develop data governance, and coach junior engineers while collaborating with product managers and business teams.

As a Data Engineer, you will create and maintain data solutions, ensuring quality and implementing ETL processes across systems.

As a Data Engineer, you will implement data pipelines and analytics to support decision-making using AWS technologies and Machine Learning.

The Data Engineer will design, develop, and maintain data solutions, create data pipelines, ensure data quality, and implement ETL processes.

The Data Engineer will build and maintain data pipelines, ensure data quality, and work with various teams in an Agile environment.

The Data Engineer II will manage and support cloud-based data platforms, ensuring stable operations and collaborating with teams for data ingestion and analytics.

Design, build, and operationalize large-scale data solutions on Google Cloud Platform, optimizing data pipelines for performance and cost with tools like Python and SQL.

As a Data Engineer I, you will design and develop data pipelines, optimize SQL queries, ensure data integrity, and collaborate with stakeholders to deliver data solutions.

As a Junior Data Engineer, you'll design and optimize data pipelines, ensure data quality, collaborate with teams, and contribute to innovative data projects.

The Data Engineer designs, develops, and maintains data pipelines and infrastructure, ensuring data accuracy and accessibility while collaborating with data teams.

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 design and develop data pipelines, ensuring data quality and scalability. You'll collaborate with teams to meet business needs and mentor junior members.

Lead the data engineering team to build scalable data pipelines, design data architecture, and collaborate with cross-functional partners. Ensure data quality and drive architectural vision aligned with business needs.

The Data Engineer is responsible for designing and maintaining data pipelines, ensuring data quality, and integrating data for analysis using advanced technologies such as Snowflake and AWS.

The Snowflake Data Engineer will develop and manage large-scale data pipelines, collaborate with stakeholders, and optimize data engineering solutions using Snowflake.

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

As a Data Engineer, you will design, build, and maintain scalable data platforms and pipelines, optimizing workflows and ensuring security.

The Azure Data Engineer role requires developing data engineering solutions using Azure technologies. Responsibilities include implementing data pipelines, performing data analysis, and collaborating with stakeholders on data-driven projects.

As a Business Intelligence Data Engineer, you'll develop scalable data architectures and models, manage data pipelines, and enhance analytics using AI tools.

The Data Automation Test Engineer will validate data migration and ETL processes while developing a QA framework, automation scripts, and collaborating with cross-functional teams.

The Data Analytics Engineer is responsible for implementing Power BI solutions, collaborating with clients, optimizing data analytics, and mentoring junior staff.

The Senior Data Engineer will develop, deploy, and maintain data products in a cloud environment, ensuring data quality and supporting analytics for internal stakeholders.

Seeking a Staff Data Engineer to design and optimize data pipelines, mentor junior engineers, and ensure data quality across cloud platforms.

Lead the design and implementation of data integration solutions using IDMC, ensure data quality, and guide junior engineers.

The Senior Data Engineer will design and optimize data processing pipelines, collaborating with teams to enhance data solutions for retail media measurement, using tools like Python and Apache Spark.