Senior Manager, Data Engineering, Semantics

Pfizer

. Own one or more Data Engineering & Semantics capability areas end to end, defining capability roadmaps, engineering standards, reusable patterns, controls, service expectations, and lifecycle outcomes across China CEI .

Posted 11/11/2026full-timeShanghai • ChinaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Data Engineering and Semantics, focusing on data governance, technical semantics, and the delivery of governed data products. Proficient in BI platforms and data quality management, with a strong understanding of China data privacy and compliance requirements.

Highest-signal resume keywords

Data EngineeringBusiness Intelligence PlatformsTechnical Data GovernanceSemantic ModelingData Quality Management

ATS Keywords

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Hard Skills

SQLDAXPower QueryDimensional ModelingData ConnectivityDashboard DevelopmentPerformance TuningData ArchitectureData ProductsAgile Delivery

Soft Skills

Clear CommunicationMentoringCollaborationDecision DocumentationContinuous Improvement

Tools & Technologies

Microsoft Power BITableauQlik Sense

Certifications & Qualifications

CSPOPSPOCSMPSMSAFe POPMSAFe Agilist

Industry Keywords

China Data PrivacyCross-Border ControlsPharmaceutical IndustryRegulated IndustryData QualityObservabilityMetadataTaxonomyOntologyAI Data Enablement

Tech Stack

Tools & technologies

SQLTableau

About the role

Key responsibilities & impact

Own one or more Data Engineering & Semantics capability areas end to end, defining capability roadmaps, engineering standards, reusable patterns, controls, service expectations, and lifecycle outcomes across China CEI
Lead and govern Data Engineering across ingestion, integration, transformation, storage, and serving for structured, unstructured, and knowledge data
Lead and govern reporting and business intelligence foundations
Lead technical management and lifecycle governance of BI platforms, including workspace and environment administration, access controls, release management, refresh reliability, performance, capacity, and license utilization
Partner with Enterprise Engineering for production operations and implement GCA DSM-approved business definitions and KPIs
Lead and govern reusable, governed data products and data agents, including the CL layer of the AI Empowered Consumption Layer and agent-facing data contracts
Lead and govern technical semantics, including semantic models, metadata, taxonomies, and technical mappings
Lead and govern data trust and reliability engineering, including technical data governance controls, shift-left data quality checks, lineage, observability, and China data, privacy, and cross-border controls
Serve as senior design authority for complex data products, semantic architectures, and data-reliability solutions
Lead data contributions to complex PODs from MVP scoping through scale
Shape capability capacity, skills mix, and partner leverage across internal, PIC, and external resources
Manage material risks and dependencies
Mentor Managers, Senior Associates, and specialists
Collaborate with the Director, Data Engineering & Semantics, team colleagues, CEI PODs, PIC, GCA DSM, AITO, Enterprise Engineering, Deployment & Operations, global data teams, and privacy, legal, and compliance stakeholders
Deliver the AICL as one POD with the AITO AI engineering team and GCA DSM
Drive timely, high-quality delivery of governed, reusable data products, semantic models, and the AICL CL layer
Improve data quality, lineage, observability, compliance with China data and privacy requirements, and POD delivery speed

Requirements

What you’ll need

Modern data engineering, data architecture, data products, and reporting and business intelligence foundations
Demonstrated hands-on expertise in at least one major BI platform, such as Microsoft Power BI, Tableau, or Qlik Sense
Platform administration, SQL, dimensional and semantic modeling, data connectivity and refresh, row-level security, dashboard development, and performance tuning
Proficiency in relevant platform-specific technologies, such as DAX and Power Query for Power BI
Governed self-service BI enablement
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
Knowledge of China data privacy and cross-border controls
Bachelor’s degree or above in Computer Science, Data Engineering, Data Science, Information Systems, or a related computing discipline
10+ years of progressive relevant experience based on a bachelor’s degree; a master’s or doctoral degree may reduce the years required
Agile delivery, product metrics, adoption measurement, and evidence-based iteration
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
Agile and product certifications are preferred, including CSPO / PSPO, CSM / PSM, and SAFe POPM or SAFe Agilist
Demonstrated ability to connect decisions to measurable business, user, service, and transformation outcomes
Ability to apply responsible AI, reuse, architecture, security, privacy, and scale principles
Ability to enable clear accountability and effective cross-functional execution across GCA DSM, AITO, Enterprise Engineering, PIC, and CEI PODs
Clear communication, decision documentation, use of evidence and telemetry, and continuous improvement