Analytics Semantic Engineers
Smart TechLink Solutions Inc.
Hartford, CT, United States
19 days ago
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Role details
Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Data Analysis
Microsoft Azure
Business Intelligence Development
Data Governance
Data Infrastructure
Graph Database
Metadata
Power BI
Tableau (Software)
Enterprise Data Management
+6 more
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.
- Strong experience in semantic modeling and enterprise data modeling., Position Title: Semantic / Analytics Engineers Location: Minneapolis, MN & Hartford, CT (Onsite) Duration: 6 Months Contract Job Description: Build and maintain data models an…
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
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