Principal Scientific Data Engineer – Informatics

Principal Scientific Data Engineer – Informatics Who we are

Kymera is a clinical-stage biotechnology company pioneering the field of targeted protein degradation (TPD) to develop medicines that address critical health problems and have the potential to dramatically improve patients’ lives. Kymera is deploying TPD to address disease targets and pathways inaccessible with conventional therapeutics. Having advanced the first degrader into the clinic for immunological diseases, Kymera is focused on building an industry-leading pipeline of oral small molecule degraders to provide a new generation of convenient, highly effective therapies for patients with these conditions.

Founded in 2016, Kymera has been recognized as one of Boston’s top workplaces for the past several years. For more information about our science, pipeline and people, please visit  or follow us on X (formerly Twitter) or Linked In.

• PIONEER
  :
  We are courageous, resilient and rigorous in our mission to improve patients’ lives through our revolutionary degrader medicines.
• COLLABORATE
  :
  We value trust + transparency from everyone. Our goals are shared, our decisions data-driven and our camaraderie genuine.
• BELONG
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  We recognize our differences, inviting curiosity and inclusivity, so that our people are valued, seen, and heard.

We are seeking a highly motivated Principal Scientific Data Engineer to lead and deliver Informatics solutions that directly support Research. This role is hands on and execution driven, with accountability for Informatics project delivery, operational data workflows, and close partnership with Research champions. The ideal candidate combines strong technical depth with pragmatic leadership, understands scientific data end to end, and can translate Research needs into scalable, reliable informatics capabilities.

• Lead and deliver Informatics projects supporting discovery from requirements through production. Act as a primary Informatics partner to Research champions; proactively identify opportunities to improve data storage, quality, and usability.
• Own and support day‑to‑day Research operations related to data management, automation, and scientific systems.
• Design, build, and maintain data pipelines, automation scripts, and analytical tools to improve operational efficiency.
• Administer, integrate, and optimize scientific data platforms (e.g., CDD Vault, D360, Live Design, or similar systems). Collaborate with IT and Cybersecurity on infrastructure, access controls, and system reliability.
• Manage external vendors and consultants: scope work, oversee delivery, review quality, and control costs.
• Work closely with IT/Informatics leadership to shape strategy and roadmap, with a strong focus on quality, scalability, maintainability, and future‑proofing.

• Master’s degree or higher in a relevant STEM field (e.g., Computer Science, Bioinformatics, Computational, Data Science, or related discipline).
• 8+ years of relevant experience in Informatics, Data Engineering, or computational roles supporting scientific research.
• Demonstrated experience leading Informatics or data‑centric projects with cross‑functional stakeholders. Experience working with and managing external vendors and consultants.
• Advanced technical experience in:
• R (including R Shiny for interactive applications)
• Python
• SQL and relational databases
• Linux command-line environments
• Experience managing and supporting scientific software platforms such as CDD, D360, Live Design, or equivalent systems.
• Strong background in data management, including data modeling, curation, validation, and lifecycle management. Proven experience wrangling and integrating open‑source or public scientific datasets.
• Working knowledge of AWS or cloud‑based infrastructure concepts.

• Experience with budgeting, forecasting, and financial tracking for Informatics initiatives.
• Prior people management or technical mentorship experience.
• Familiarity with additional programming languages or frameworks beyond R and Python.
• Understanding of the Chemistry DMTA (Design‑Make‑Test‑Analyze) cycle and its data flows.
• Experience with proteomics data…