Top Data Engineer Jobs in Gurgaon

The Data Engineer designs and implements scalable data processes, manages data pipelines, assists data scientists, and supports the organization's cloud strategy while leading junior engineers.

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

The Big Data Engineer II is responsible for designing and maintaining data pipelines on cloud and on-premises, ensuring data quality and compliance, collaborating with stakeholders, and utilizing big data frameworks and cloud platforms.

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.

As a Data Engineer, you'll optimize data pipelines and models using PySpark, SQL, and GCP. Responsibilities include processing large datasets and designing enterprise-scale data platforms.

The Data Engineer / Analytics Engineer will build scalable data models and pipelines using dbt and Snowflake while collaborating with stakeholders and engineers.

The Data Engineer will build and maintain data pipelines, ensuring data quality and performance, while collaborating with engineering and product teams in an Agile environment.

The Data Engineer will optimize SQL queries, build ETL data pipelines, clean data, and support database design to prepare datasets for reporting and AI/ML applications.

The Data Engineer is responsible for implementing business logic in the Data Warehouse, designing ETL pipelines, optimizing data loading processes, and collaborating with stakeholders to improve data architecture.

We are seeking Data Engineers to migrate dashboards from Hadoop to GCP, ensuring data consistency, accuracy, and collaborating with cross-functional teams.

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

Design, build, and optimize scalable data pipelines on Azure using Databricks and Spark. Implement CI/CD, performance tuning, debugging, and collaborate with stakeholders to deliver production-grade data solutions.

Design, implement, and manage data infrastructure, build ETL/ELT pipelines, and collaborate with stakeholders to support analytics and BI initiatives.

The Data Engineer is responsible for developing ETL/ELT pipelines, managing data warehousing, processing data with Python, and collaborating with stakeholders to meet data needs.

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

As a Senior Analyst-Data Engineer, you will design, develop, and optimize data pipelines, ensure data quality and transform marketing data into insights.

Lead the maintenance and expansion of reporting platforms, develop data transformations in SQL, manage junior engineers, and ensure data quality on Google Cloud Platform.

Assist in designing and implementing scalable data processes, develop data pipelines, support ETL from multiple sources, and enable data-driven business solutions.

The Data Engineer will design, build, and maintain ETL/ELT pipelines, ensuring data quality, security, and compliance while collaborating across multiple teams.

Design and build data infrastructure and architecture, optimize data processes, implement ELT applications, and develop high-quality data pipelines for clients.

Lead data architecture and pipeline design, promote engineering best practices, mentor team members, implement ETL/streaming solutions (Airflow, dbt, Airbyte), ensure data governance and reliability, and collaborate with product, analytics, and engineering to deliver scalable data solutions.

The Data Engineer designs and develops data pipelines for storage and processing, optimizes data integration, and collaborates with analysts on data models and KPIs, while leveraging cloud and AI technologies.

The Senior Data Engineer will build and optimize data pipelines in Azure Databricks, migrate existing pipelines from Azure Synapse, and design scalable data models to support a financial services client's data platform modernization.

Design, build, and optimize scalable data pipelines and analytics solutions using Microsoft Fabric, PySpark, Python, and SQL. Collaborate with stakeholders, manage data governance, and ensure data quality in a Lakehouse architecture.