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
