Analytics Semantic Engineers

Role -Analytics Semantic Engineers

Client - UHG

Key Responsibilities

• Own the architecture, design, and implementation of the enterprise semantic layer .
• Translate complex source and enterprise data models into business-friendly semantic models.
• Define standardized business entities, dimensions, measures, metrics, KPIs, hierarchies, relationships, and business rules .
• Establish a consistent definition and calculation methodology for enterprise metrics and KPIs.
• Partner with Finance and business stakeholders to define authoritative financial and operational measures.
• Develop and maintain the enterprise business glossary , including business terms, definitions, ownership, and usage.
• Establish semantic models that provide a consistent foundation for BI, reporting, analytics, and AI/GenAI consumption .
• Define semantic standards for financial reporting, management reporting, operational reporting, and analytical use cases.
• Ensure consistency between the semantic layer, underlying enterprise data models, and source-system definitions.
• Work with Data Architects and Data Engineers to ensure semantic models are supported by reliable and governed data.
• Establish mappings between business terminology and physical data assets, including tables, columns, APIs, data products, and source systems.
• Define reusable semantic models that can support multiple BI tools and analytical applications.
• Support self-service analytics by making trusted business concepts and metrics easily discoverable and understandable.
• Collaborate with AI/ML teams to enable semantic context for GenAI, RAG, knowledge retrieval, and intelligent analytics .
• Evaluate and leverage appropriate semantic technologies, including semantic modeling frameworks, metadata platforms, knowledge graphs, ontologies, and metrics layers where appropriate.
• Establish governance processes for semantic definitions, metric changes, approvals, ownership, and version management.
• Identify and resolve inconsistencies in business definitions, calculations, and reporting logic across functions.
• Create documentation and standards for semantic modeling and metric development.
• Provide architectural leadership and guidance to BI developers, data engineers, analysts, and business users.
• Strong experience in semantic modeling and enterprise data modeling .
• Proven experience designing and implementing semantic layers, metrics layers, or business-oriented analytical models .
• Strong understanding of metrics, KPIs, dimensions, measures, hierarchies, relationships, and business rules .
• Experience developing and managing an enterprise business glossary .
• Strong understanding of financial reporting and accounting concepts.
• Experience working with Finance, FP&A, Accounting, or other finance-related business functions.
• Understanding of BI architecture and analytical consumption patterns.
• Experience with modern data platforms such as Snowflake, Databricks, Azure , or comparable platforms.
• Experience with semantic/BI technologies such as Power BI, Tableau, Looker, dbt Semantic Layer, Cube, or comparable technologies.
• Understanding of metadata, data lineage, data governance, and data quality.
• Ability to translate business requirements into robust and reusable semantic models.
• Strong stakeholder-management and communication skills, with the ability to bridge business and technical teams