Job#:2184 - Lead Data Engineer – Data Product
Job Description:
Job Title: Lead Data Engineer – Data Product (Onshore)
Job Summary
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.
Key Responsibilities
- 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.
Required Skills
- 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 DevOps CI/CD, and version-controlled database deployments (DDL).
Preferred Skills
- Experience with Kimball and Data Vault data modeling methodologies.
- Healthcare domain experience, including Claims, Electronic Health Records (EHR), or related healthcare data.
- Strong communication, leadership, and stakeholder management skills.
