Senior Associate Director, Data Engineering & Analytics

Payer Sciences; Chicago (IL); Hybrid; USD 73,000 - 113,000; Full time

Benefits offered by this job

Medical coverage

Dental

Vision

401k

Parental leave

Tuition reimbursement

Job summary

Payer Sciences is seeking an Associate Director, Data Engineering to design and maintain data infrastructure for pharma clients. You’ll work on large healthcare datasets and partner with Analytics and Strategy teams to ensure data is accessible and analysis-ready.

This hybrid role supports data quality, documentation, and process improvements, with responsibilities spanning ETL/ELT pipelines, data governance, and collaboration across technical and business teams in a dynamic environment.

Qualifications

• 3–5 years of professional experience.
• Hands-on experience with SQL and Python or R.
• Foundational exposure to cloud platforms (Snowflake, Redshift, Azure), ETL/ELT tools, APIs, and Git.
• Experience with structured healthcare or pharma data preferred.
• Bachelor’s degree in Computer Science, Data Engineering, Analytics or other related discipline.

Responsibilities

• Design, build, and maintain data pipelines and ETL/ELT processes.
• Ingest and integrate claims, coverage, SP/HUB, contracting, and other third-party datasets.
• Implement data quality controls, governance, and security protocols.
• Document data schemas, transformations, and workflows.
• Collaborate with Data Analysts and Strategists to provide access to curated datasets.
• Troubleshoot data issues and escalate risks as needed.

Skills

SQL

Python or R

Data transformation concepts

Data analysis across sources

Pharma data familiarity

Communication

Detail oriented

Education

Bachelor's degree in CS/Data Eng/Analytics

Tools

Snowflake

Redshift

Azure

ETL/ELT tools

APIs

Git

Job description

Payer Sciences is seeking an Associate Director, Data Engineering to design and maintain data infrastructure for pharma clients. You’ll work on large healthcare datasets and partner with Analytics and Strategy teams to ensure data is accessible and analysis-ready.

This hybrid role supports data quality, documentation, and process improvements, with responsibilities spanning ETL/ELT pipelines, data governance, and collaboration across technical and business teams in a dynamic environment.