Senior Data Engineer — Translational Data Products

Challenging. Meaningful. Life-changing. Those aren't words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You'll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible. Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us .

Our team builds and maintains data products that make R&D data usable and AI-ready: biomarker, biospecimen, clinical trial, omics, among others, assembled into governed, curated, linked, documented, AI-ready products that translational scientists and analysts use for insight generation and decision making. You will own data products end to end - from documenting where the data lives, to unlocking the source system with its data owner, through entity mapping, modeling and validation, to making sure the product answers high-value scientific questions and gets used or retired. You will work alongside data scientists, machine learning engineers, and translational medicine stakeholders, and you will use Claude Code as a normal part of how you deliver. What you will do ·

Design, build, test, and maintain ETL/data normalization pipelines on Databricks and AWS that create governed, well-documented datasets in Unity Catalog (both tables and views). ·

Work directly with data owners and governance partners to bring new sources under governance and make them AI-ready - cataloged, described, permissioned, quality- checked, and discoverable. This may include csv, tsv, json, xlsx, powerpoint, structured documents, etc. ·

Engage stakeholders in translational medicine, biomarker sciences, predictive medicine, reverse translation and clinical development to understand and translate the high value questions they are trying to answer into robust data product designs and data maps linking sources to targets (STTM). ·

Turn a scientific or business question into a data model and a mapping from the question to the SQL query; carefully describe data constraints / context and considerations into caveats that a stakeholder can understand. ·

Bring a test-driven, validation-driven mindset: expectations and data quality checks in the pipeline, reconciliation against source, unit and regression tests that run automatically in GitHub Actions on every pull request, and documented evidence that a number is correct before anyone depends on it. ·

Create the hooks, guardrails, CDK / CloudFormation infrastructure as code, and automated checks that keep our work reliable and aligned with BMS enterprise IT standards - SDLC, security, SSO / identity and access management, mandatory resource tagging and service registration (CRID, ISR assessment), code review, secrets handling, change management. Run the required cyber checks - dependency, container and infrastructure-as-code scanning (Wiz, Dependabot) on every pull request - and respond quickly when a vulnerability is reported, remediating critical findings within BMS Cybersecurity timelines. ·

Prepare feature-ready and model-ready datasets, and support ML and GenAI workloads built on top of our products; support deployment and accessibility of data products on NVIDIA clusters. ·

GitHub-based development, pull requests, code review, automated build/test/deploy pipelines (continuous integration and delivery, CI/CD), infrastructure as code. ·

Work with stakeholders to ensure the data products continue to meet their expectations as their work evolves and needs change.

· Requires a Bachelor's degree in a relevant discipline along with 4+ yrs of relevant work experience. · Demonstrated experience building production data pipelines (ETL/ELT) at scale. ·

- complex joins, window functions, performance tuning, and the judgment to know when a query result is wrong. · Python for data engineering and data science. ·

experience - S3, IAM, Glue, Lambda, ECS and Fargate. ·

- package a Python service in Docker and ship it to ECS/Fargate through infrastructure as code (AWS CDK / CloudFormation) and a GitHub Actions pipeline, with health checks, secrets from parameter store, and SSO / OIDC authentication. Our MCP servers, which expose data products to AI agents, are deployed this way and you will maintain your own. ·

practice: monitoring, alerting, incident response. ·

fluency: branching, pull requests, code review, and GitHub Actions. ·

- unit tests that run in the pipeline, plus regression and reconciliation checks that run against the platform (a Databricks job or SQL check) so a pull request fails when a number changes. Point to a validation suite you built and say what it caught. ·

- git, shell, the AWS and Databricks CLIs, and daily hands-on use of

to drive a task end to end. Claude Code is the approved agentic coding tool here; other agents are not permitted at this time. ·

- hands-on experience with clinical, molecular and assay data: patient-level clinical data and lab results, molecular data (genomics, transcriptomics, proteomics), and assay output (biomarker panels, flow cytometry). You know how these data types link to a patient and where they are commonly misinterpreted. Translational or biomarker work is welcome but not expected. ·

You work directly with translational scientists and data owners without a translator: following the biology and study design well enough to ask the next question, and continuing to ask until you know what decision the data has to support. You say so when the question as asked will not answer the need, and you trace data upstream to its original source of truth - how it entered the organization, which system captured it first, what was changed along the way, and who owns it.

·

domain experience specifically. · Fluency in

- SDTM/ADaM, EDC - and comfort with exploratory / non-CDISC research data where no standard applies. ·

- Unity Catalog, Delta Lake, Lakeflow/DLT pipelines, Databricks SQL. · Depth in a specific

(genomics, transcriptomics, proteomics, flow cytometry), or experience with digital pathology / imaging data. · Experience

, not only using it - hooks, guardrails, skills, subagents, or automated review steps you built for a team to reuse. · Experience partnering with machine learning engineers on feature pipelines or RAG/GenAI data preparation. · Data governance and metadata management experience (lineage, data contracts, cataloging, access models). If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

Cambridge Crossing: $118,650 - $143,778 Princeton - NJ - US: $107,870 - $130,707 Tampa - FL - US: $107,870 - $130,707 The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee's work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience. Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/. Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include: •

Medical, pharmacy, dental, and vision care. •

Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP). •

401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.

T he summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program.

With a single vision as inspiring as "Transforming patients' lives through science™ ", every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.

BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role: Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.

BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com . Visit careers.bms.com/ eeo -accessibility to access our complete Equal Employment Opportunity statement.

BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area. If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/

We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection . Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations. If you believe that the job posting is missing information required by local law or incorrect in any way, please contact BMS at TAEnablement@bms.com . Please provide the Job Title and Requisition number so we can review. Communications related to your application should not be sent to this email and you will not receive a response. Inquiries related to the status of your application should be directed to Chat with Ripley. R1605529 : Senior Data Engineer - Translational Data Products