Lead Data Engineer – Data Product

We are seeking an experienced Lead Data Engineer to drive the design, development, and delivery of enterprise Data Products in the GOLD layer using a Data Product Factory approach. The ideal candidate will lead data engineering initiatives, mentor a team of engineers, and build scalable, high-quality data products for analytics and AI use cases.

• Lead the design and development of 5 source-aligned Data Products and 2 MVP Data Products
  .
• Set up and manage dbt projects, including profiles, sources, seeds, and models across RAW, CURATED, and GOLD layers.
• Develop reusable anonymization macros using SHA-256 hashing across multiple data sources.
• Publish Data Products, manage catalog registration, and capture data lineage in Horizon
  .
• Collaborate with the Gen AI Engineering team to expose GOLD-layer Data Products to AI/BI semantic layers.
• Lead sprint planning, backlog grooming, code reviews, and mentor a team of 4+ data engineers.
• Ensure adherence to coding standards, CI/CD practices, and enterprise data governance.

• 8–12 years of experience in Data Engineering, including 4+ years in a technical leadership role
  .
• Expertise in Snowflake SQL
  , dbt (Core/Cloud), and Python
  .
• Strong experience with Azure Data Factory (ADF) orchestration,
  Snowpipe
  , COPY INTO
  , and Dynamic Tables
  .
• Deep understanding of Data Product design patterns, including FAIR principles and Data Contracts
  .
• Hands‑on experience with Git
  , Azure Dev Ops CI/CD
  , and version‑controlled database deployments (DDL).

• Experience with Kimball and Data Vault data modeling methodologies.
• Strong communication, leadership, and stakeholder management skills.

ClinDCast offers Healthcare IT solutions and consulting services to payers, providers and life sciences organizations enabling them to enhance care delivery to patients.