# Manager, Data Engineering & Semantics at Pfizer

Pfizer is hiring a Manager, Data Engineering & Semantics in Shanghai, China. Level rates it Little AI ●○○○; you can [apply on Pfizer](https://jobsbylevel.com/go/a000a353-bafa-4200-913b-bf18f266d059?utm_medium=ai-agent).

AI Level 1, AI centrality 25 out of 100. China - Shanghai - Shanghai.

## Details

- Company: [Pfizer](https://jobsbylevel.com/companies/pfizer)
- AI level: AI Level 1 (score 25 out of 100)
- Location: China - Shanghai - Shanghai
- Posted: November 11, 2026
- Apply: https://jobsbylevel.com/go/a000a353-bafa-4200-913b-bf18f266d059?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=manager-data-engineering-semantics-at-pfizer-a2e0e2

## Description

1. Role Summary The Manager is a delivery owner within Data Engineering & Semantics, and may be assigned to a specific capability or deployed into a cross-functional CEI POD based on portfolio priorities. The role combines hands-on data engineering, data product and data quality delivery with backlog, quality, readiness and stakeholder accountability, including delivery of the AICL CL layer. 2. Key Accountabilities Manage day-to-day delivery for assigned data engineering, data product, semantic or data-quality outcomes. Own day-to-day delivery of Data Engineering across L1–L4 — ingestion, integration, transformation, storage and serving for structured, unstructured and knowledge data, and reporting and business intelligence foundations. Own day-to-day delivery of reusable, governed data products and data agents, including the CL layer of the AI Empowered Consumption Layer (AICL) and agent-facing data contracts. Own day-to-day delivery of technical semantics — semantic models, metadata, taxonomies and technical mappings that implement DSM-approved business definitions and harmonized KPIs. Own day-to-day delivery of Data Trust & Reliability Engineering — technical data governance controls, shift-left data quality checks, lineage, observability and China data, privacy and cross-border controls. Maintain clear backlog, dependencies, risks, acceptance criteria, test evidence, documentation and transition plans. Coordinate with GCA DSM on definitions and issue resolution, with Enterprise Engineering, PIC and partners on productionization, and coach Senior Associates. 3. Required Capabilities & Competencies Modern data engineering, data architecture, data products and reporting and business intelligence foundations. Hands-on proficiency in one or more mainstream BI platforms (e.g. Microsoft Power BI, Tableau, Qlik Sense or SAP Analytics Cloud), including data connectivity and integration, semantic modeling, dashboard and report development, access controls, refresh management and performance optimization, implementing DSM-approved business definitions and KPIs. Semantic modeling, metadata, taxonomy and ontology; knowledge and unstructured data engineering; data enablement for AI retrieval and agents. Technical data governance, data quality, lineage and observability, and China data privacy and cross-border controls. Outcome ownership: connects decisions to measurable business, user, service and transformation outcomes. AI-first and enterprise-minded: applies responsible AI, reuse, architecture, security, privacy and scale principles appropriate to the work. POD collaboration: enables clear accountability, effective cross-functional execution and minimal handoff friction across GCA DSM, AITO, Enterprise Engineering, PIC and CEI PODs. Precision and learning: communicates clearly, documents decisions, uses evidence and telemetry and continuously improves delivery. Bachelor’s degree or above in Computer Science, Data Engineering, Data Science, Information Systems or a related computing discipline. 8+ years of progressive relevant experience based on a bachelor’s degree, where a master’s or doctoral degree may reduce the years required, with scope and judgment consistent with this role. Agile delivery, product metrics, adoption measurement and evidence-based iteration. Agile and product certifications are preferred (e.g. CSPO / PSPO, CSM / PSM, and SAFe POPM or SAFe Agilist for scaled-agile environments). Demonstrated ability to work across business, product, technology, data and governance stakeholders in a matrixed environment. 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, Data Engineering & Semantics and team colleagues, CEI PODs and PIC. GCA Data Strategy & Management (DSM) owns AICL business requirements, business definitions, unified KPIs, master data business rules and

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/manager-data-engineering-semantics-at-pfizer-a2e0e2

Source: https://jobsbylevel.com/jobs/manager-data-engineering-semantics-at-pfizer-a2e0e2

## Cite this page

Level. https://jobsbylevel.com/jobs/manager-data-engineering-semantics-at-pfizer-a2e0e2.

Get job alerts: https://jobsbylevel.com/newsletter