Description

Key Responsibilities

• Design, develop, and maintain scalable ETL/data pipelines and warehouse solutions.
• Build and orchestrate workflows using Airflow.
• Develop data solutions using Python, SQL, Spark, Kafka, Trino/Dremio, Iceberg, and Docker.
• Monitor, troubleshoot, and support production pipelines, including incident response, backfills, and deployments.
• Perform root cause analysis (RCA) and resolve issues across shared data platforms.
• Implement data quality checks, monitoring, and validation frameworks.
• Collaborate with Data Engineering, Sales, and Finance teams to deliver reliable data solutions.
• Maintain Git, CI/CD, and SDLC best practices.

Required Qualifications

• 5+ years of Data Engineering or Software Engineering experience with a strong data focus.
• Strong SQL and Python skills.
• Hands-on experience with Airflow, Spark, Kafka, Trino/Dremio, Iceberg, Docker, and ETL/data pipeline development.
• Experience supporting production data pipelines, DataOps, incident management, and data quality.
• Strong troubleshooting, documentation, and communication skills.

Preferred Qualifications

• Java or Scala experience.
• Experience with AWS, Azure, or GCP.
• Experience with Sales or Finance analytics.
• Experience using AI coding tools such as Claude, ChatGPT, or GitHub Copilot

Key Skills

Education

Bachelor's degree