Senior Manager, Data Engineering & Semantics

The Senior Manager, Data Engineering & Semantics, is a capability leader within Data Engineering & Semantics, owning one or more capability areas, such as Data Engineering, Data Product Management, or Data Trust & Reliability Engineering.

The role turns DSM-led business requirements into trusted, governed, and AI-ready data, including the CL layer of the AI Empowered Consumption Layer (AICL), so that reporting, analytics, and AI solutions work from one consistent data foundation.

Key Accountabilities:

• Own one or more team 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 L1–L4 , ingestion, integration, transformation, storage, and serving for structured, unstructured, and knowledge data, and 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.
• Lead and govern 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.
• Lead and govern Technical Semantics , semantic models, metadata, taxonomies, and technical mappings that implement DSM-approved business definitions and harmonized KPIs.
• Lead and govern Data Trust & Reliability Engineering , 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, and 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.

Required Capabilities & Competencies:

• Modern data engineering, data architecture, data products, and reporting and business intelligence foundations.
• Demonstrated hands-on expertise in at least one major BI platform (e.g., Microsoft Power BI, Tableau, or Qlik Sense).
• Semantic modeling, metadata, taxonomy, and ontology.
• Technical data governance, data quality, lineage, and observability.
• 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.
• Agile delivery, product metrics, adoption measurement, and evidence-based iteration.

Measures of Success:

• Timely, high-quality delivery of governed, reusable data products, semantic models, and the AICL CL layer.
• Consistent implementation of DSM-approved business definitions and harmonized KPIs across reporting, analytics, and AI.
• Improved data quality, lineage, observability, and adherence to China data and privacy requirements.
• Faster POD delivery through trusted, reusable, and AI-ready data.