Job title: Senior Data Engineer
Job type: Contract
Contract Length: 12 months
Rate: $60-70 per hour
Role Location: United States

The Company:

US healthcare technology company that has spent the last decade building software for hospitals and their medical device suppliers. Their platform takes manual, paper heavy steps out of how products are sourced, tracked and paid for around surgical procedures. They have recently raised new capital to expand the team.

Role & Responsibilities:

They are investing in their data platform and need a Senior Data Engineer to take ownership of a Databricks-based analytics stack. You will join a small team with a lot of autonomy and visibility, turning platform data into trusted models, reporting and AI-assisted analytics for customers and internal teams. This is greenfield ownership of a modern stack.

Key Responsibilities:

• Design and maintain a star-schema warehouse and lakehouse in Databricks
• Build and scale dbt pipelines, covering models, tests and source management
• Develop a semantic layer that serves both BI and AI-driven analytics
• Tune pipeline performance and control compute cost
  Own CI/CD for the data platform, including automated data-quality and dashboard validation and promotion from Dev to Staging to Production
• Bring in data from internal services and customer systems on AWS
• Work with product, operations and leadership to turn business questions into dependable data products
• Set data engineering standards and mentor teammates as the team grows

Core Requirements

• 5+ years of data engineering experience
• Strong hands-on Databricks experience (Delta Lake,
• Spark/SQL, Unity Catalog or similar)
• Production dbt experience at scale
• Advanced SQL and Python
• Dimensional modelling and warehouse design (star schema)
• Experience with AWS data services
• CI/CD and testing practices for data pipelines
• Clear communicator who is comfortable owning work in a startup setting

Preferred Experience

• Experience with BI or semantic layer tools such as Looker or similar
• Exposure to AI/LLM-driven analytics or natural-language querying
• Background in healthcare, medtech, supply chain or B2B SaaS
• Familiarity with HIPAA and healthcare data security

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