Description

You will design, build, and maintain data pipelines for data transformation and aggregation.

Responsibilities

• Design, develop, and maintain ETL pipelines to transform raw data into actionable datasets.
• Optimize complex SQL queries and Python scripts for data processing speed across various database environments.
• Integrate disparate data sources, including JSON and relational warehouses, into a unified data layer.
• Build and execute automated QA test suites using Python to validate data completeness and accuracy.
• Manage data repositories and CI/CD pipelines to ensure governed deployment of data assets.

Required Skills

• 5+ years of experience building and running ETL pipelines in production.
• Expert proficiency in Python and SQL for data manipulation and automated testing.
• Experience with relational and non-relational databases (Postgres, MySQL, DynamoDB, Cassandra).
• Hands-on experience with AWS services (S3, Glue, Lambda, IAM).
• Experience building automated QA frameworks for data validation.
• Familiarity with data orchestration tools (Airflow, Prefect) and Git.
• Experience handling unstructured data (JSON) transformation.
• Master’s Degree in a quantitative or technical field.

Key Skills

Education

Any Graduate