Data Engineer - Scalable ETL, PySpark & Airflow on GCP

Tata Consultancy Services Limited; Herndon (VA); On-site; USD 100,000 - 120,000; Full time

Benefits offered by this job

Discretionary Annual Incentive.

Comprehensive Medical Coverage:Medical

Dental & Vision

Disability Planning & Insurance

Pet Insurance Plans.

Maternal & Parental Leaves.

Aut & Home Insurance options.

Identity Theft Protection.

Commuter Benefits

Certification & Training Reimbursement

Job summary

Tata Consultancy Services Limited in Herndon, VA seeks a Data Engineer to design, build, govern, and optimize data platforms, pipelines, and integrations for analytics, reporting, AI/ML, and business operations.

You will develop scalable ETL/ELT pipelines, automate ingestion from multiple sources, and build PySpark-based data processing with Airflow workflows, Hive and Kafka-based data solutions. Strong governance and incident support are required.

Qualifications

• Design, build, and maintain scalable ETL/ELT pipelines.
• Automate data ingestion from multiple data sources.
• Develop and optimize PySpark-based data processing frameworks.
• Build and manage Airflow workflows and orchestration pipelines.
• Work with Hive and Kafka-based batch and streaming data solutions.
• Implement data quality, monitoring, governance, and operational controls.
• Support production incidents, performance tuning, and continuous improvement initiatives.

Responsibilities

• The Data Engineer will be responsible for designing, building, governing, and optimizing data platforms, pipelines, and integrations to ensure secure, reliable, and scalable data availability for analytics, reporting, AI/ML, and business operations.

Skills

Kafka

Python

PySpark

Airflow

Hive

GCP

ETL Testing

Job description

Tata Consultancy Services Limited in Herndon, VA seeks a Data Engineer to design, build, govern, and optimize data platforms, pipelines, and integrations for analytics, reporting, AI/ML, and business operations.

You will develop scalable ETL/ELT pipelines, automate ingestion from multiple sources, and build PySpark-based data processing with Airflow workflows, Hive and Kafka-based data solutions. Strong governance and incident support are required.