AI Data Engineer

The role is for an AI Data Engineer who will build the governed semantic and knowledge foundation that enables AI agents and end users to work from consistent business definitions, trusted metrics, and reusable analytics logic.

This role will own the design and governance of a semantic layer that captures business entities, relationships, metrics, dimensions, hierarchies, glossary terms, lineage, and validation rules across priority analytics domains. This semantic foundation will power AI-driven analytics use cases such as metric design, natural-language search, self-service reporting, dashboard generation, and executive narrative creation

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The ideal candidate combines strong analytics engineering and data modeling experience with a deep understanding of metric governance, business semantics, and how trusted definitions support both human and AI consumers. This role is central to ensuring that AI outputs are accurate, explainable, and aligned with IHH business meanin

• g.
  Build governed semantic la
• yerMetric certification and validation workf
• lowBusiness glossary and semantic mapping for AI (glossary, synony
• ms)Expose semantic definitions for BI and age
• ntsDocumentation, lineage, versioning and change managem

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REQUIREME

• NTS:Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related f
• ield4–7 years of experience in data engineering, analytics engineering, or related r
• olesProven experience working with data warehousing and transformation pipel
• inesDemonstrated experience in data modeling and building analytics-ready data
• setsExposure to semantic layer / metrics layer development in enterprise environm
• entsStrong proficiency in SQL (expert level) and Py
• thonSolid experience in data modeling (dimensional modeling, star schema, medallion architect
• ure)Hands-on experience building and maintaining ETL/ELT pipel
• inesFamiliarity with cloud data platforms (Azure, Databri