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Role Description

This role involves developing and optimizing RWD/HEOR pipelines and delivering high-quality, tailored RWE deliverables with speed and accuracy.

• Design, build, and maintain robust ETL pipelines for real-world healthcare data (EMR, claims, registries, etc.)
• Develop data models and schemas optimized for RWE analytics with detailed documentation
• Translate project requirements into technical needs, evaluating/modifying current pipelines, algorithms, need for custom data fields as necessary
• Ensure data quality, integrity, and compliance with HIPAA and other regulatory standards
• Follow data governance and security best practices
• Algorithm development in alignment with organizational needs (e.g., device mapping, phenotyping, etc.)
• Contribute to the identification of opportunities for new processes, technical products and drive the development of green-lit projects
• Partner closely with informaticists, 3PH Cloud team, and internal regulatory, compliance, and clinical affairs
• Audit-ready detailed documentation of ETL, HEOR pipelines, and other data engineering or data science processes
• Provide expert opinion and/or assist during the requirements gathering for future RWD datasets, RWE software platforms, or organizational technology stack

Qualifications

• 5+ years in engineering and maintaining data pipelines involving healthcare real-world datasets (claims, EMR, etc.)
• Experience in clinical research, health economics and outcomes research (HEOR), or real-world data (RWD) environments—ideally including time at a CRO, or medical device company
• Proficiency in Python, SQL, and data pipeline tools
• Familiarity with issues of data quality, bias, and regulatory defensibility using RWD
• Familiarity with clinical coding systems (ICD, CPT, SNOMED, RxNorm, etc.)
• Experience partnering with cross-functional teams with competing priorities
• Exceptional written and verbal communication skills with a proven ability to communicate complex material to audiences of varying technical backgrounds
• Comfortable operating in ambiguity, setting priorities, and driving execution in a startup/growth-stage environment

Requirements

• Advanced degree in data science, engineering, informatics, epidemiology, or related field with strong emphasis on quantitative methods (e.g., MPH, MS, PhD)
• Experience with cloud platforms and data lakes (Azure/AWS/GCP)
• Proficiency in machine learning frameworks, computable phenotypes
• Familiarity with OMOP common data model, HL7 FHIR
• Working knowledge of post-market evidence needs in the medtech industry, including MDR/Vigilance, FDA RWE guidance, and/or EU CER deliverables

Location and Travel Requirements

• This is a fully remote position and may be performed anywhere within the United States of America
• Occasional domestic travel may be required for company meetings, audits, etc.