Data Engineer

Experience: 4 to 14 Years
Locations: Gurgaon | Bangalore | Chennai | Pune
Work Mode: On-site
Shift: US Shift / US Business Hours
Employment Type: Contractual
Salary: As per industry standards

Job Description

We are looking for experienced Data Engineers to design, build, and maintain scalable data platforms and pipelines supporting enterprise applications and analytics.

The ideal candidate should have strong experience in data engineering, ETL/ELT, cloud technologies, databases, and distributed data processing, along with the ability to work with global and US-based teams.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows.
• Build and optimize data ingestion, transformation, and integration processes.
• Work with large and complex datasets to ensure data quality, reliability, and availability.
• Develop data solutions using Python, SQL, and relevant data engineering technologies.
• Design and maintain data models, data warehouses, and data lakes.
• Optimize data pipelines and queries for performance and scalability.
• Integrate data from multiple sources including APIs, databases, applications, and external systems.
• Implement data quality, validation, monitoring, and governance processes.
• Collaborate with Data Scientists, Analysts, Architects, Developers, QA, and business stakeholders.
• Troubleshoot data pipeline and production issues and perform root-cause analysis.
• Participate in technical design and architecture discussions.
• Work closely with US-based teams and stakeholders during US business hours.

Required Skills

• 4 to 14 years of overall IT experience, with relevant Data Engineering experience.
• Strong hands-on experience with Python and SQL.
• Experience with ETL/ELT tools and data pipeline development.
• Strong knowledge of relational databases such as Oracle, PostgreSQL, MySQL, or SQL Server.
• Experience with data warehousing and data modeling concepts.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with distributed data processing technologies such as Spark / PySpark.
• Strong understanding of data integration, transformation, and data quality.
• Experience working in Agile/Scrum environments.
• Strong analytical and problem-solving skills.
• Good communication and stakeholder-management skills.

Good to Have

• Databricks.
• Snowflake.
• Kafka / Event Streaming.
• Airflow.
• AWS Glue / Azure Data Factory.
• Hadoop ecosystem.
• Kubernetes and Docker.
• CI/CD and DevOps practices.
• Experience in BFSI / Banking / Payments / Financial Services.
• Experience working with US-based clients or global teams.