Data Engineer, PCCTC

Memorial Sloan Kettering Cancer Center (MSK) is dedicated to ending cancer for life through innovative research and clinical care. They are seeking a Data Engineer to join the Prostate Cancer Clinical Trials Consortium, where the role involves designing and maintaining data storage and access infrastructure for clinical trials, ensuring data is organized and available for analysis.

Responsibilities:

• Implement and maintain relational database structures for clinical trial data storage in AWS S3, using tools such as DuckDB and/or DuckLake
• Build and maintain ETL pipelines that ingest data from clinical trial data systems (e.g. EDCs), transforming raw clinical data into organized, versioned, analysis-ready datasets
• Develop access layers (database connectors, internal R packages or utilities) that enable our R-focused Data Science Team to query and retrieve data efficiently
• Implement and maintain access management and permissioning structures across data systems, including SharePoint and Airtable, ensuring consistent and scalable controls as the team and trial portfolio grow
• Maintain data governance standards, including naming conventions, versioning, and documentation, across our active trial portfolio
• Collaborate with Clinical Operations and Data Management teams to understand data flows from sites and ensure upstream processes align with downstream analytic needs
• Use GitHub Enterprise for version control and contribute to CI/CD workflows for pipeline automation where infrastructure allows

Requirements:

• An undergraduate degree, preferably in computer science, data engineering, information systems, or a related field
• 2–4 years of experience building or maintaining data pipelines, ETL processes, or database systems
• Working knowledge of SQL and relational database concepts
• Familiarity with cloud storage (AWS S3 preferred) and infrastructure-as-code principles
• Experience with access management, permissioning, or user administration across collaborative platforms
• Exposure to version control (git/GitHub)
• Passion for data and creating reliable systems that empower cancer care and clinical research
• Strong problem-solving and analytical thinking skills with the ability to troubleshoot complex data and system issues
• Excellent collaboration and communication skills, with the ability to work effectively across technical and non-technical teams
• Highly organized with strong attention to detail and a commitment to data accuracy, quality, and documentation
• Ability to manage multiple priorities in a fast-paced environment while meeting deadlines
• Proactive, adaptable, and eager to learn new technologies and contribute to continuous process improvement
• Self-motivated and able to work independently in a fully remote environment while remaining an engaged team member
• CDISC data standards (SDTM, ADaM) and how clinical trial data is structured
• DuckDB, DuckLake, or similar analytical database technologies complex & relational data sets
• R (you won't need to be an R programmer, but understanding how R users consume data will make you more effective)
• Airtable structure and maintenance (we have several operational data systems here)
• SharePoint administration and file system permissioning at scale
• CI/CD for orchestrating automated data pipelines
• Clinical trial data lifecycle, from EDC capture through analysis-ready datasets