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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data engineering, including ingestion, transformation, and SQL, while ensuring data quality and governance. Proficient in developing semantic models and collaborating across teams to deliver reliable data products and solutions.
Highest-signal resume keywords
Data Engineering ExperienceSQL ProficiencyPython ProgrammingSemantic Models DevelopmentData Governance Implementation
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data IngestionData TransformationData ModelingBusiness IntelligenceData QualityData LineageTechnical DocumentationData Access for AI RetrievalTechnical Specifications CreationData Mapping
Soft Skills
Detail-OrientedCollaborative MindsetLearning OrientationEffective CommunicationProblem-Solving
Tools & Technologies
AI-Assisted Engineering ToolsData Pipeline Monitoring ToolsData ProductsGoverned Data AgentsObservability Tools
Industry Keywords
Pharmaceutical IndustryData PrivacyChina Technology EnvironmentRegulated Industry ExperienceCross-Border Data Controls
Tech Stack
Tools & technologiesPythonSQL
About the role
Key responsibilities & impact- Execute assigned work within Data Engineering & Semantics capability squads and CEI PODs
- Build, test, document, monitor, and support reliable data pipelines, data products, and AICL CL-layer components
- Support data engineering across ingestion, integration, transformation, storage, and serving for structured, unstructured, and knowledge data
- Support reusable, governed data products and data agents, including the AICL CL layer and agent-facing data contracts
- Develop and maintain semantic models, metadata, taxonomies, and technical mappings implementing approved business definitions and harmonized KPIs
- Implement 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
- Escalate blockers promptly
- Collaborate with the Director, CEI PODs, PIC, GCA DSM, AITO AI engineers, Enterprise Engineering, Deployment & Operations, business units, and governance partners
- Transition dependable solutions to production and improve quality, reuse, and team efficiency
Requirements
What you’ll need- Hands-on data engineering experience covering ingestion, transformation, SQL, Python, data modeling, 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
- Application of 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; 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