IT Data Engineer(Semantic Layer & Data Products)

该职位来源于猎聘 Job Description Summary The IT Service Professional – Semantic Layer & Data Products is responsible for designing, building, and maintaining enterprise semantic models and data products. This role does not focus on front-end dashboard design; instead, it serves as the architect of the company’s trusted business language. You will build the governed foundation of reusable KPIs, business logic, and scalable data models that power downstream Reporting, Advanced Analytics, and future AI-driven / AI Agent use cases. Key Responsibilities

• Enterprise Semantic Modeling: Design, develop, and maintain governed, highly scalable enterprise semantic models and data products rather than building individual, ad-hoc reports.
• Business Logic & KPI Implementation: Translate complex business processes and stakeholder requirements into reusable business logic, standardized calculations, and unified enterprise KPIs.
• Cross-Functional Architecture Alignment: Ensure absolute consistency across reporting, analytics, and emerging AI use cases by adhering strictly to data standards and core architecture principles.
• Performance Optimization: Continuously optimize semantic models and data products for maximum scalability, fast query usability, and high performance across massive data volumes.
• Governance & Lifecycle Management: Enforce data quality, strict naming conventions, semantic asset documentation, and formal KPI certification processes to maintain a trusted data foundation.
• Data & AI Team Collaboration: Work closely with Data Engineers to ensure proper pipeline integration and collaborate with AI teams to design AI-ready semantic structures.
• Self-Service Enablement: Support enterprise-wide self-service and analytics initiatives by delivering intuitive, reusable semantic assets that empower business users to build their own insights safely.

Qualifications

• Education & Experience: Bachelor’s degree in an IT-related major (e.g., Computer Science, Data Science, Information Technology, or Information Systems) paired with 3 to 5 years of professional working experience in a data environment.
• Core Modeling Expertise: Strong, proven experience in dimensional data modeling and designing enterprise-level semantic layers (e.g., Semantic Data Engineer, Analytics Engineer, or Modeling-focused BI Engineer).
• Advanced Languages: Advanced knowledge of DAX (Measures, Evaluation Context, Performance tuning) and strong SQL skills for data manipulation and querying.
• Microsoft Ecosystem Proficiency: Deep hands-on experience with Microsoft Fabric, Power BI Semantic Models, and modern Microsoft data technologies.
• Modern Data Architecture: Strong understanding of Data Warehouse, Lakehouse, and Data Product architecture, with basic Python skills to support data engineering concepts.
• Business & KPI Acumen: Exceptional ability to analyze complex business processes, master data, and enterprise data concepts to translate them seamlessly into technical models.
• Stakeholder Communication: Strong collaborative and communication skills, with the ability to bridge the gap and speak the language of both business stakeholders and deeply technical teams.
• Engineering Mindset: A quality-oriented, structured thinker focused entirely on standardization, code reusability, and continuous technical learning.