Innovation, Data & Analytics Team, Data Engineer

Scorpion Therapeutics; Cambridge (MA); Hybrid; USD 130,000 - 185,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Pfizer is seeking a senior data engineer to develop and maintain production data pipelines supporting AI-driven analytics and agentic workflows. You will build, monitor, and optimize data platforms (Databricks, Snowflake) and implement canonical data models while ensuring governance and data conformance.

Role requires 6+ years in data engineering (or 5+ with a Master’s), strong SQL/Python skills, cloud experience, and collaboration across data science, governance, and engineering teams in a

Qualifications

• 6+ years in data engineering or 5+ years with a Master’s degree.
• Expertise in SQL, Python, cloud platforms, and ETL/ELT design.
• Experience with healthcare data is a plus.

Responsibilities

• Build, monitor, and optimize data pipelines and platforms.
• Collaborate with analysts, scientists, and engineers to validate data conformance and improve performance.
• Document architecture for governance and data management.

Skills

SQL

Python

Cloud platforms

ETL/ELT design

Education

Bachelor's degree in data engineering

Master's degree in data engineering

Tools

Databricks

Snowflake

Job description

Role: Develop and maintain production data pipelines supporting Pfizer's AI-driven analytics and agentic workflows, ensuring high-quality, reliable, and timely data delivery.

Responsibilities

• build, monitor, and optimize data platforms (e.g., Databricks, Snowflake);
• implement canonical data models like OMOP/HEDIS;
• collaborate with data analysts, scientists, and engineers to validate data conformance, meet analytical needs, and improve pipeline performance;
• document architecture for governance.

Requirements

• 6+ years (Bachelor's) or 5+ years (Master's) in data engineering, with expertise in SQL, Python, cloud platforms, and ETL/ELT design;
• healthcare data experience (claims, EHR, HEDIS/OMOP) preferred.

High-Value: focus on healthcare/pharma sector, supporting AI/ML workflows, with hybrid work setup across multiple U.S. locations; role involves cross-functional collaboration with data science, governance, and engineering teams in a regulated environment.