Top Data Engineer Jobs in Gurgaon

The Data Engineer 2 will develop and maintain data pipelines, support analytics, build data models, and enhance data quality for strategic insights.

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

The Senior Data Engineer is responsible for developing and maintaining data pipelines, supporting analytics across products, and transforming business requirements into technical solutions. They will also manage a team of engineers and analysts.

As a Data Engineer III, you will design and optimize ETL pipelines, develop data models with BigQuery, and implement data workflows using Apache Airflow while collaborating with teams.

The Senior Data Engineer will design and implement data ingestion processes, develop scalable data pipelines, and collaborate with teams to integrate data sources.

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

The Data Engineer II will design and implement data pipelines, manage data architecture, and collaborate with teams to deliver analytics solutions.

As an Azure Data Engineer, you will build and maintain data platforms, develop data pipelines, manage data lakes, and ensure security and compliance.

The Data Engineer II role involves building scalable ETL pipelines, reporting, and managing data workflows using tools like Python, Azure, and BI tools such as Power BI.

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 will design and maintain data infrastructure, optimize performance, support data-driven decisions, and collaborate across 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.

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.

Design and manage data pipelines and architectures using cloud platforms. Collaborate with stakeholders to ensure data security and compliance, optimizing workflows for performance.

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

The role involves developing data models in SAP Data Sphere, enhancing reporting capabilities, and collaborating with stakeholders to support financial analytics and data solutions.

Join YipitData as a Senior Data Pipeline Engineer, building and maintaining data pipelines, collaborating on solutions and optimizing data processes, with a focus on Spark and SQL.

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

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

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.

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

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