Data Engineer (Innovation, Data & Analytics)

Quick Facts - Role: Data Engineer for Innovation, Data & Analytics - Focus: Production data pipelines enabling AI-based analytics and agentic workflows - Work setup: Hybrid (2–3 days/week on site) - Locations: NYHQ, PA-Collegeville, MA-Cambridge, CT-Groton, Europe sites, or QC–Montreal - Employment authorization: Permanent authorization in the U.S.; no U.S. visa sponsorship (TN/O-1/H-1B, etc.) Description Build and operate production data pipelines that power the Innovation, Data & Analytics team’s AI-based workflows. You will implement the canonical data model, ensure reliable and timely high-quality data, and support downstream analytical and agentic systems. You will also own production reliability, monitoring, incident response, and data quality. Responsibilities - Build and maintain data pipelines aligned to data model and standards set by Governance & Compliance - Own production reliability for cloud data platforms (e.g., Databricks, Snowflake), including monitoring and incident response - Implement canonical data model in production, including OMOP/HEDIS mappings where applicable - Support agentic workflows with clean, timely, well-structured data - Collaborate with Senior Data Analyst to validate model and mapping conformance - Collaborate with Senior Data Scientist and AI/ML Engineer to ensure pipelines meet analytical/model needs - Flag data quality issues and recommend solutions - Identify opportunities to improve pipeline performance, cost, and maintainability - Document pipeline architecture and data flows for governance and audit Requirements - Degree in Computer Science, Data Engineering, Information Systems, or related field - 6+ years of data engineering experience with a Bachelor's degree OR 5+ years with a Master's degree - Strong SQL and Python - Experience with cloud data platforms (Databricks, Snowflake, or similar) - Experience designing and orchestrating ETL/ELT pipelines - Healthcare data experience (claims, EHR, HEDIS/OMOP) preferred - Effective English verbal and written communication for scientific/technical, regulatory, and business audiences Benefits - Eligible for Global Performance Plan bonus (target 17.5% of base salary) - Participation in share-based long-term incentive program - Comprehensive benefits including 401(k) with matching contributions and additional retirement savings contribution - Paid vacation, holidays, personal days; paid caregiver/parental and medical leave - Health benefits: medical, prescription drug, dental, vision coverage - Relocation package: not eligible formatted_html_description:

Quick Facts

• Role: Data Engineer (Innovation, Data & Analytics)
• Focus: Production data pipelines enabling AI-based analytics and agentic workflows
• Work setup: Hybrid (2–3 days/week on site)
• Locations: NYHQ, PA-Collegeville, MA-Cambridge, CT-Groton, Europe sites, or QC–Montreal
• Employment authorization: Permanent authorization in the U.S.; no U.S. visa sponsorship

Description

Build and operate production data pipelines that power the Innovation, Data & Analytics team’s AI-based workflows. You will implement the canonical data model, ensuring reliable, timely, high-quality data for downstream analytics and agentic systems. You will also own production reliability, including monitoring, incident response, and data quality.

Responsibilities

• Build and maintain data pipelines aligned to the data model and standards defined by Governance & Compliance
• Own production reliability of cloud data platforms (e.g., Databricks, Snowflake), including monitoring and incident response
• Implement canonical data model in production, including OMOP/HEDIS mappings where applicable
• Support agentic workflows with clean, timely, well-structured data
• Partner with the Senior Data Analyst to validate data model and mapping conformance
• Partner with the Senior Data Scientist and AI/ML Engineer to ensure pipelines meet analytical and agentic needs
• Flag data quality issues and advise on required solutions
• Identify opportunities to improve pipeline performance, cost, and maintainability
• Document pipeline architecture and data flows for governance and audit

Requirements

• Degree in Computer Science, Data Engineering, Information Systems, or a related field
• 6+ years in data engineering with a Bachelor’s degree OR 5+ years with a Master’s degree
• Strong SQL and Python
• Experience with cloud data platforms (Databricks, Snowflake, or similar)
• Experience designing and orchestrating ETL/ELT pipelines
• Healthcare data experience (claims, EHR, HEDIS/OMOP) preferred
• Effective English verbal and written communication across scientific/technical, regulatory, and business audiences

Benefits

• Bonus eligibility under the Global Performance Plan (target 17.5% of base salary)
• Eligibility for share-based long-term incentive program
• 401(k) plan with matching contributions and additional retirement savings contribution
• Paid vacation, holiday, and personal days; paid caregiver/parental and medical leave
• Health benefits including medical, prescription drug, dental, and vision coverage