Description

You will design, develop, test, and maintain scalable ETL data pipelines.

Responsibilities

• Design, develop, test, and maintain scalable ETL data pipelines using Python.
• Perform data ingestion from various sources and apply transformation and cleansing logic.
• Implement and enforce data quality checks, validation rules, and monitoring.
• Collaborate with data scientists, analysts, and engineering teams to deliver data solutions.
• Manage version control using GitHub and participate in CI/CD pipeline deployments.

Required Skills

• 7–10 years of hands-on experience in Python for backend or data engineering projects.
• Strong working experience with GCP services (Dataflow, BigQuery, Cloud Functions, Cloud Composer).
• Solid understanding of data pipeline architecture, integration, and transformation techniques.
• Experience in Apache Spark, Kafka, Fast APIs, Airflow, and GCP Composer DAGs.
• Strong experience in SQL with at least one enterprise database (SQL Server, Oracle, PostgreSQL).
• Experience with storage technologies including MongoDB and Redis.
• Experience in data migrations from on-premise data sources to Cloud platforms.
• Experience in working with version control systems like GitHub and CI/CD practices.

Key Skills

Education

Bachelor’s degree