Sr. Engineer, Data
Skills
Computer ScienceDevopsData ServicesDatabasesDocument ProcessingGlueMaster Data Management
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor’s degree in a related field or equivalent experience
- 8+ years in data engineering, data architecture, or related disciplines
- 5+ years designing modern lakehouse architectures with Azure Databricks, Delta Lake, ADLS Gen2, and Unity Catalog
- Experience leading enterprise data architecture, canonical data modeling, data governance, and master data management
- Strong hands-on experience with Apache Spark, PySpark, SQL, Python, DataOps automation, and CI/CD pipelines
- Experience supporting machine learning, AI, generative AI, RAG, and AI-ready data platforms preferred
- Experience modernizing legacy SQL-based ETL, reporting, and data warehouse environments
- Experience with healthcare data domains such as claims, eligibility, pharmacy, clinical, operational, provider, financial, and regulatory data preferred
- Experience mentoring engineers and conducting architecture reviews
- Knowledge of Data Mesh, Data Products, Medallion Architecture, Event-Driven Architecture, and Lakehouse Governance preferred
- Hands-on experience with AWS and Azure data services and infrastructure
- Experience working within regulated environments supporting HIPAA, HITRUST, SOC 2, NIST, or similar frameworks preferred
Nice to have
- Technical leadership
- Cross-functional collaboration
- Mentorship
- Architectural thinking
- Governance mindset
- Healthcare domain knowledge
- AI curiosity
- Modernization focus
Day to day
- Serve as the technical lead for enterprise data engineering and lakehouse modernization initiatives
- Design and implement Azure Databricks based lakehouse architectures with Delta Lake, ADLS Gen2, and Unity Catalog
- Develop governed canonical data models, reusable data products, and AI-ready datasets that support analytics, automation, and machine learning