Innovation, Data & Analytics Team, Data Engineer

Role: Data engineer responsible for building and maintaining production data pipelines supporting AI-driven workflows within a biopharma environment, ensuring high-quality, reliable data for analytics and agentic systems. Responsibilities: develop and oversee data pipelines aligned with governance standards, maintain platform reliability (e.g., Databricks, Snowflake), implement canonical data models including OMOP/HEDIS mappings, and support downstream analytical processes. Collaborate across data science, analytics, and governance teams to validate data quality, optimize pipeline performance, and document architecture. Qualifications: Bachelor's or Master's in Computer Science, Data Engineering, or related field with 5+ to 6+ years' experience in healthcare or pharma data engineering; strong SQL and Python skills; expertise with cloud data platforms and ETL/ELT design; healthcare data experience (claims, EHR, HEDIS/OMOP) preferred. High-Value: focus on healthcare data within pharma, supporting AI/ML workflows, with hybrid work in US locations (NY, PA, MA, CT, Europe, Montreal). The role emphasizes operational independence, strategic thinking, and cross-functional engagement in a regulated, fast-paced environment.