Description

You will lead the modernization of a 20-year-old SQL-based enterprise data warehouse to Databricks, focusing on full re-engineering of ETL pipelines and data models rather than a lift-and-shift migration.

This role is remote.

Responsibilities

• Architect and build scalable data models and ETL pipelines on Databricks to support AI builds.
• Migrate legacy SQL-based EDW workloads, including SSAS cubes, to modern cloud-native architectures.
• Implement API data ingestion and raw data processing using Python and Kafka.
• Integrate data workflows with Azure Data Factory and legacy tools like DataStage.
• Ensure BI readiness for downstream consumption by Cognos, Tableau, and Thoughtspot.

Required Skills

• 7+ years of hands-on experience with Databricks and advanced SQL.
• Strong proficiency in Python for data processing and Kafka ingestion.
• Experience with Azure Data Factory (ADF) and ETL tools such as DataStage.
• Understanding of No-SQL databases and API data ingestion patterns.
• Familiarity with BI platforms including SSAS, Cognos, Tableau, or Thoughtspot.
• 5+ years of total software development and deployment experience.

Preferred Skills

• Experience designing scalable data architecture specifically for AI workloads.

Key Skills

Education

Any Graduate