Description
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, and 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.
- 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.
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