Senior Data Engineer, Translational Data Products

Bristol Myers Squibb

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Tampa, FLCambridge, MAPrinceton, NJ
Salary: $118,650–$143,778 / yr
Posted: 17 days ago
Freshness: Confirmed live yesterday
Closes: Oct 30, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $172k

This role $131k

$108k most similar roles pay here $222k

This role pays less than 75% of similar roles. Most pay $131,812–$211,200 — the shaded band above. At the midpoint, this role pays about $131k versus about $172k for comparable roles.

Based on 240 similar postings.

Employer

About Bristol Myers Squibb

Bristol Myers Squibb is a global biopharmaceutical company committed to discovering, developing and delivering innovative medicines to patients.

Bristol Myers Squibb currently has 33 open roles on FindRole.

Listed pay typically runs $125,480–$152,049 across 33 roles with salary data.

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View all roles at Bristol Myers Squibb

At a glance

TL;DR · Senior Data Engineer, Translational Data Products

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The Senior Data Engineer — Translational Data Products joins a team dedicated to building and maintaining data products that make R&D data, such as biomarkers and clinical trial results, usable and AI-ready for translational scientists. You will own data products end-to-end by designing, building, and maintaining ETL pipelines on Databricks and AWS while ensuring datasets are governed and documented in Unity Catalog. Key responsibilities include unlocking source systems, translating scientific questions into technical data models, and implementing a test-driven validation mindset using GitHub Actions. The role requires proficiency in SQL, Python, and AWS services like S3, Glue, and Lambda. You will also manage containerized deployments via Docker and infrastructure as code. Essential domain expertise includes handling life sciences data, including clinical, molecular, and assay outputs to solve complex problems in translational medicine and biomarker sciences.

What does a Data Engineer earn?

Median $183138 from 214 postings across 58 companies.

See salary data

Skills

SQL Python AWS Databricks Unity Catalog Docker CloudFormation CI/CD GitHub Actions ETL ELT GenAI Claude Code S3 Lambda ECS Fargate Shell Git

What you'll do

Build, operate, and maintain ETL/data normalization pipelines on Databricks and AWS to create governed datasets.
Unlock data access by collaborating with owners to bring new sources under governance and make them AI-ready.
Translate complex scientific questions from stakeholders into robust data product designs and mapping models.
Implement a test-driven development approach using automated unit, regression, and reconciliation tests in GitHub Actions.
Engineer infrastructure as code using CDK or CloudFormation to ensure systems meet enterprise IT standards.
Prepare feature-ready and model-ready datasets to support machine learning and generative AI workloads.
Manage data products end-to-end by documenting source locations, performing entity mapping, and validating data quality.
Perform routine cyber security checks and remediate vulnerabilities within established corporate timelines.

What we're looking for

Bachelor's degree in a relevant discipline and 4+ years of relevant work experience.
Demonstrated experience building production data pipelines (ETL/ELT) at scale.
Very strong SQL skills including complex joins, window functions, and performance tuning.
Proficiency in Python for data engineering and data science.
Experience with AWS services including S3, IAM, Glue, Lambda, ECS, and Fargate.
Experience deploying containerized services using Docker, infrastructure as code (AWS CDK/CloudFormation), and GitHub Actions.
Fluency in GitHub, command-line tools, and the use of Claude Code for task execution.
Hands-on experience with life sciences data including clinical, molecular, and assay data.
Experience with Databricks, Unity Catalog, or Delta Lake (preferred).
Familiarity with clinical trial data standards like SDTM/ADaM (preferred).
Experience in translational medicine, biomarker sciences, or specific omics modalities (preferred).