Senior Scientific Data Engineer, R&D Data Platform

Abbott Laboratories; Northern (KY); Hybrid; USD 78,000 - 156,000; Full time

Job summary

Abbott Laboratories is seeking a Senior Scientific Data Engineer to lead end‑to‑end data solutions for cancer diagnostics research. You’ll build reusable tools and workflows to organize, validate, transform, analyze, and share complex data across genomic, clinical, imaging, and lab datasets.

The role blends software engineering with scientific data work, collaborating with researchers, data scientists, and DevOps partners to define scalable platform capabilities and standards.

Qualifications

• Bachelor’s degree in computer science, data science, engineering, statistics, mathematics, bioinformatics, computational science, or another relevant quantitative discipline.
• 5+ years of relevant professional or applied research experience, or 3+ years with an advanced degree.
• Advanced programming skills in Python.
• Strong SQL skills and experience with structured and semi‑structured data.
• Demonstrated track record of building reusable, maintainable software.
• Experience designing data pipelines, Python packages, APIs, notebooks, or internal tools.
• Substantial hands‑on experience using AWS for data processing and analytics.
• Depth in AWS services and architecture to evaluate options with DevOps/engineering partners.
• Experience conducting quantitative research or ML-related activities.
• Experience cleaning/integrating/validating data from multiple sources at scale.
• Familiarity with Git, testing, documentation, CI/CD.

Responsibilities

• Lead design and delivery of reusable tools and services for ingesting, validating, transforming, documenting, discovering, and sharing scientific data.
• Own platform capability areas end to end including design, adoption, and maintenance.
• Develop Python/SQL solutions: packages, data pipelines, APIs, notebooks, and lightweight apps.
• Create self‑service workflows enabling researchers with varying coding skills to prepare data.
• Translate research needs into a prioritized technical roadmap with scientists and DevOps.
• Establish data harmonization standards across diverse sources and drive adoption.
• Design automated data quality and validation checks before downstream use.
• Improve data documentation, traceability, and discoverability of datasets.
• Evaluate AWS services for scientific data workflows and architecture.

Skills

Python programming

SQL

Data pipelines

APIs

Notebooks

Spark/PySpark

Education

Bachelor’s degree in a quantitative field

Tools

AWS services (S3, Athena, Glue, EMR, Lambda, SageMaker)

Job description

Abbott Laboratories is seeking a Senior Scientific Data Engineer to lead end‑to‑end data solutions for cancer diagnostics research. You’ll build reusable tools and workflows to organize, validate, transform, analyze, and share complex data across genomic, clinical, imaging, and lab datasets.

The role blends software engineering with scientific data work, collaborating with researchers, data scientists, and DevOps partners to define scalable platform capabilities and standards.