Description

You will design, build, and maintain production-grade data pipelines and engineering workflows.

This role is on-site.

Responsibilities

• Design, develop, and lead data engineering teams to deliver robust data solutions.
• Build and maintain complex data pipelines using Python and PySpark.
• Schedule and monitor workflows using Apache Airflow.
• Implement CI/CD pipelines for data engineering projects using GitHub and Docker.
• Drive TDD practices by writing automated unit and integration tests.

Required Skills

• 7+ years of overall IT experience with a strong Data Engineering background.
• 5+ years building production data pipelines with Python and PySpark.
• Strong expertise in Airflow for DAG management and scheduling.
• Hands-on experience with TDD and automated testing frameworks.
• Proficiency in Git for version control (branching, merging, PRs).
• Solid SQL experience for data ingestion and analytics.
• Experience with Unix/Linux environments and strong command-line skills.
• Experience with containerization (Docker) and cloud platforms (GCP preferred).

Preferred Skills

• Experience with OpenShift, Cloudera, Tableau, Confluence, and Jira.

Key Skills

Education

Bachelor's degree