The Science Office within Abbott Cancer Diagnostics is seeking a Senior Scientific Data Engineer to lead the design and delivery of practical data solutions for cancer research and diagnostic development. This position sits at the intersection of software engineering, scientific data, and applied analysis. You will own significant pieces of our research data platform end to end, building reusable tools and workflows that help researchers organize, validate, discover, transform, analyze, and share complex data. These solutions may include Python packages, data pipelines, APIs, notebooks, workflow utilities, and lightweight web applications. This is not a traditional enterprise data warehousing position. The work centers on heterogeneous research data generated across scientific programs, including genomic, clinical, imaging, laboratory, and experimental data. Successful candidates will combine deep technical skills with an understanding of how quantitative research is conducted, and will be comfortable setting technical direction when a problem is still loosely defined. You will work closely with scientists, data scientists, bioinformaticians, software engineers, and R&D DevOps partners, and will often represent the team in cross-functional technical discussions. The ideal candidate is curious, resourceful, and able to turn ambiguous scientific needs into durable, reusable capabilities, while helping other engineers do the same.
