Top Data Engineer Jobs in Gurgaon

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 Engineer will analyze HR data, build data pipelines from systems like Workday and Greenhouse, and support analytics for business decisions.

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

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.

The Data Engineer will build and maintain data pipelines, ensuring data quality for AI, machine learning, and data science applications. Responsibilities include data ingestion, processing, and collaboration for high-quality dataset delivery.

As a Data Engineer, you'll design and maintain ETL pipelines, integrate data, ensure data quality, and collaborate in an Agile environment.

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

Build infrastructure tools for trading, optimize data delivery, implement process improvements, ensure data monitoring and reporting, and write efficient code.

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

As a Data Engineer, you will create and maintain data pipelines, support data scientists, and design data solutions on cloud platforms.

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

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.

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.

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 will design and maintain data pipelines and infrastructure, collaborate with teams, and ensure data accuracy for client solutions.

The Freelance Data Engineer will analyze data, design databases, manage data operations, and collaborate on data-driven projects to optimize data infrastructure.

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

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

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

Analyze business requirements for data visualization, design and maintain PowerBI dashboards, integrate data using SQL and Snowflake, and enhance processes.

Lead the evolution of decentralized data infrastructure, design and maintain ETL/ELT pipelines, and collaborate across teams to derive insights from data.

The role involves designing, developing, and maintaining large scale data engineering solutions while collaborating with stakeholders on data governance and analytics.

The Data Architect Engineer will lead the development of reliable data pipelines using Databricks and AWS, collaborating with cross-functional teams.

The Lead Data Engineer at Leapwork will design, implement, and manage scalable data architectures, lead teams, and optimize database performance while ensuring data integrity and quality.