Senior Scientific Data Engineer, Research Platform

Abbott; Illinois; On-site; USD 78,000 - 156,000; Full time

Job summary

Abbott seeks a Senior Scientific Data Engineer to lead the design and delivery of practical data solutions for cancer research and diagnostic development. You will own end-to-end research data platform capabilities, building reusable tools, pipelines, APIs, and lightweight apps to organize, validate, transform, analyze, and share complex data.

You will collaborate with scientists, data scientists, bioinformaticians, engineers, and DevOps partners to translate ambiguous needs into durable

Qualifications

• Bachelor in CS, data science, engineering, or related quantitative field.
• 5+ years of relevant experience, or 3+ years with an advanced degree.
• Proficient Python programming and strong SQL for structured data.
• Experience with AWS for data processing and analytics.
• Experience building reusable software and data pipelines.

Responsibilities

• Lead design and delivery of reusable data tools and services.
• Own platform capabilities end to end, including design and maintenance.
• Develop Python/SQL data pipelines, APIs, notebooks, and apps.
• Create self-service workflows for researchers with varying skills.
• Collaborate with scientists to translate needs into a technical roadmap.
• Establish standards for data harmonization across sources.
• Design automated data quality and validation frameworks.
• Mentor engineers through code reviews and design feedback.
• Communicate progress to technical and leadership audiences.

Skills

Python

SQL

AWS

Git

Data modeling

REST APIs

Spark/PySpark

Mentoring

Education

Bachelor's degree in CS or related quantitative field

Advanced degree in a relevant field

Tools

Spark

PySpark

SageMaker

AWS Glue

Job description

Abbott seeks a Senior Scientific Data Engineer to lead the design and delivery of practical data solutions for cancer research and diagnostic development. You will own end-to-end research data platform capabilities, building reusable tools, pipelines, APIs, and lightweight apps to organize, validate, transform, analyze, and share complex data.

You will collaborate with scientists, data scientists, bioinformaticians, engineers, and DevOps partners to translate ambiguous needs into durable