Senior Scientific Data Platform Engineer (Remote)

Thornton Tomasetti; United States; Remote; USD 78,000 - 156,000; Full time

Job summary

Abbott is seeking a senior data engineer to lead the design and delivery of reusable data tools across ingest, validation, and discovery. You will own platform capabilities end-to-end, developing solutions in Python and SQL, and building self-service workflows for researchers with varying coding experience.

You will leverage AWS services such as S3, Athena, Glue, EMR, Lambda, and SageMaker, mentor engineers, and collaborate with scientific teams to standardize data and improve data quality.

Qualifications

• Bachelor’s degree in a quantitative field or related discipline.
• 5+ years of relevant professional or applied research experience (or 3+ with advanced degree).
• Advanced programming skills in Python.
• Strong SQL skills with structured/semi-structured data.
• Proven track record building reusable, maintainable software.

Responsibilities

• Lead design and delivery of reusable tools for ingesting, validating, transforming, documenting, discovering, and sharing scientific data.
• Own platform capabilities end-to-end, including design, implementation, adoption, and maintainability.
• Develop maintainable solutions using Python and SQL, including data pipelines, APIs, and internal tools.
• Create self-service workflows for researchers with varying programming experience.
• Mentor engineers through code review and documentation.

Skills

Python

SQL

AWS

Spark/PySpark

Data pipelines

Git

Documentation

Education

Bachelor’s degree in a quantitative field

Tools

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

Job description

Abbott is seeking a senior data engineer to lead the design and delivery of reusable data tools across ingest, validation, and discovery. You will own platform capabilities end-to-end, developing solutions in Python and SQL, and building self-service workflows for researchers with varying coding experience.

You will leverage AWS services such as S3, Athena, Glue, EMR, Lambda, and SageMaker, mentor engineers, and collaborate with scientific teams to standardize data and improve data quality.