Description

You design, build, and maintain production-grade data pipelines and warehouse solutions.

This role is on-site.

Responsibilities

• Develop and operate custom ETL pipelines using Python, Spark, and Airflow.
• Ensure data quality through validation checks and root-cause analysis of discrepancies.
• Troubleshoot and resolve production incidents across the shared pipeline estate.
• Manage release activities, deployments, and backfills in production environments.
• Document operational processes including change plans, RCAs, and runbooks.

Required Skills

• 5+ years of data engineering or software engineering with a strong data focus.
• Expert-level SQL proficiency.
• Strong Python skills; Java or Scala is a plus.
• Experience with distributed processing (Spark) and query engines (Trino/Dremio).
• Familiarity with Kafka, Iceberg, and Docker.
• Hands-on experience with CI/CD, Git, and SDLC best practices.
• Ability to operate in AWS or GCP cloud environments.
• Strong operational discipline with rigorous environment separation.

Preferred Skills

• Experience owning ambiguous problems from start to finish with limited oversight.
• Proven track record of independent root-cause analysis for upstream issues.

Key Skills

Education

Any Gradute