Analytics Semantic Engineers

Smart TechLink Solutions Inc.

East Hartford, CT, United States

14 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

$109,300.0 - $180,200.0

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Microsoft Azure Business Intelligence Development Data Governance Data Infrastructure Data Migration Graph Database Metadata Power BI Tableau (Software)

+7 more

Enterprise Data Management Snowflake Data Layers Data Lineage Looker Analytics Software Version Control Databricks

Job description

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.
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Requirements

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

Benefits & conditions

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