Data Management Lead- Data Consumption & Semantic Layer

The Data Management Lead – Consumption & Semantic Layer is responsible for defining and operationalizing enterprise data consumption standards across the Lakehouse ecosystem. This role bridges enterprise data platforms and business users by transforming data into trusted, reusable, and governed data products through semantic models, certified datasets, and standardized access patterns. The role will drive consistency, performance, and adoption across reporting and analytics platforms while enabling a single source of truth for enterprise decision-making. Key Responsibilities Own the enterprise consumption layer, including semantic models, certified datasets, and reporting assets. Define and implement standardized data access and consumption patterns. Establish governance, service levels, and operational standards for data consumption. Partner with Data Governance to ensure consistent business definitions and a single source of truth. Enable self-service analytics through scalable and governed data products. Drive performance optimization and adoption across Tableau, Power BI, WebFocus, and other BI platforms. Key Deliverables Enterprise Semantic Layer Strategy & Standards Data Consumption Playbook (Design, Governance, and Operating Model) Certified BI Dataset Catalog (Tableau, Power BI, WebFocus) Performance and Optimization Standards for Semantic Models and BI Assets Consumption SLA & Governance Framework Enterprise Metrics and Business Definitions Repository Success Measures Increased adoption of certified datasets and semantic models Improved consistency and trust in enterprise reporting Reduced duplication of metrics and reporting logic Scalable self-service analytics with strong governance controls Achievement of established performance and service-level targets Preferred Experience Leadership experience in enterprise data management, analytics, or BI environments Expertise in semantic modeling, data consumption architecture, and data governance Experience with Lakehouse, modern data platforms, and enterprise reporting tools Strong ability to influence stakeholders and lead cross-functional initiatives Proven track record delivering scalable, governed data products and analytics solutions Hours & Work Schedule Hours per Week: 40 Work Schedule: Monday-Friday Hybrid: 4 days per week on-site, 1 day remote