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Senior Associate, Data Engineering & Semantics

Pfizer

Senior Associate, Data Engineering & Semantics

Posted An Hour Ago

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4 Locations

In-Office

Senior level

Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical

We’re in relentless pursuit of breakthroughs that change patients’ lives.

The Role

Build, test, document, monitor, and support data pipelines, data products, semantic models, and data quality controls. The role covers ingestion, transformation, storage, reporting foundations, metadata, lineage, observability, privacy, security, and AI-facing data contracts. It collaborates with engineering, governance, business, and AI teams to deliver reliable, governed data solutions in a regulated environment.

Summary Generated by Built In

Role Snapshot
Function / Team: Commercial Excellence & Innovation (CEI) - Digital & Technology (Data Engineering & Semantics)
Location: China
Grade / Level: Senior Associate
Reports to: Director, Data Engineering & Semantics
1. Role Summary
The Senior Associate is a hands-on specialist within Data Engineering & Semantics, executing assigned work within capability squads and CEI PODs across data engineering, data products, technical semantics and data quality.
The role builds, tests, documents and supports reliable data pipelines, data products and AICL CL-layer components under established architecture, security, privacy and governance standards.
2. Key Accountabilities

Deliver assigned data engineering, data product or data-quality work to agreed acceptance criteria and quality standards.

Contribute hands-on build, testing, documentation, monitoring or support for Data Engineering across L1-L4 - ingestion, integration, transformation, storage and serving for structured, unstructured and knowledge data, and reporting and business intelligence foundations.

Contribute hands-on build, testing, documentation, monitoring or support for Data Product Management - reusable, governed data products and data agents, including the CL layer of the AI Empowered Consumption Layer (AICL) and agent-facing data contracts.

Contribute hands-on build, testing, documentation, monitoring or support for Technical Semantics - semantic models, metadata, taxonomies and technical mappings that implement DSM-approved business definitions and harmonized KPIs.

Contribute hands-on build, testing, documentation, monitoring or support for Data Trust & Reliability Engineering - technical data governance controls, shift-left data quality checks, lineage, observability and China data, privacy and cross-border controls.

Use approved AI-assisted engineering and analysis tools with rigorous human verification.

Create technical specifications, data mappings, test evidence and reusable knowledge assets, and escalate blockers promptly.

3. Required Capabilities & Competencies

Hands-on data engineering - ingestion, transformation, SQL and Python, data modeling and reporting and business intelligence foundations.

Working knowledge of semantic models, metadata, data products, data quality, lineage and data access for AI retrieval.

Documentation, observability and lifecycle basics, applying privacy and security practices.

Hands-on POD delivery and collaboration with GCA DSM, AITO engineers, production engineering, PIC and partners.

Reliable, detail-oriented delivery with clear documentation and a collaborative, learning mindset.

Bachelor's degree or above in Computer Science, Data Engineering, Data Science, Information Systems or a related computing discipline.

5+ years of progressive relevant experience based on a bachelor's degree, where a master's or doctoral degree may reduce the years required.

Experience in the pharmaceutical or another highly regulated industry, and the China technology, data, privacy or vendor environment, is preferred.

4. Key Collaboration
The role works with the Director and team colleagues, CEI PODs and PIC, works with GCA DSM on business definitions and with AITO AI engineers on AICL data needs, partners with Enterprise Engineering, Deployment & Operations for production integration, and engages relevant Business Units and governance partners as needed.
5. Measures of Success

Timely, high-quality delivery of assigned data engineering and data product tasks.

Reliable, well-tested and well-documented pipelines and data products.

Effective POD contribution with dependable transition to production.

Reusable knowledge assets that improve quality, reuse and team efficiency.

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers .
Information & Business Tech

Skills Required

Hands-on data engineering experience with ingestion, transformation, SQL, Python, data modeling, reporting, and business intelligence foundations.
Working knowledge of semantic models, metadata, data products, data quality, lineage, and data access for AI retrieval.
Knowledge of documentation, observability, lifecycle practices, privacy, and security controls.
Bachelor's degree or higher in Computer Science, Data Engineering, Data Science, Information Systems, or a related computing discipline.
At least 5 years of progressive relevant experience with a bachelor's degree; a master's or doctoral degree may reduce the required years.
Experience in the pharmaceutical industry or another highly regulated industry, and familiarity with the China technology, data, privacy, or vendor environment.

What the Team is Saying

Pfizer Compensation & Benefits Highlights

Healthcare Strength — Healthcare coverage is described as comprehensive, with multiple plan options, dental and vision, mental-health services, telehealth, and eligible Pfizer medications at no cost. Family-building benefits such as infertility treatment, adoption, and surrogacy support further reinforce the offering.
Retirement Support — Retirement support includes a 401(k) with employer matching plus an additional company retirement contribution, alongside access to financial-planning resources. This combination is positioned as a meaningful part of total rewards.
Leave & Time Off Breadth — Paid time off includes 15 holidays, three to six weeks of vacation depending on service, and the option to purchase additional vacation weeks, plus dedicated caregiver-leave days. Twelve weeks of paid parental leave and backup care resources add flexibility for family needs.

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The Company

HQ: New York, NY

121,990 Employees

Year Founded: 1848

What We Do

Our purpose ensures that patients remain at the center of all we do. We live our purpose by sourcing the best science in the world; partnering with others in the healthcare system to improve access to our medicines; using digital technologies to enhance our drug discovery and development, as well as patient outcomes; and leading the conversation to advocate for pro-innovation/pro-patient policies.

Why Work With Us

We are the inventors, the problem solvers, the big thinkers — those who surmount any hurdle to deliver breakthrough medicines to the people who are counting on them the most.