BI Engineering and Enablement Director; Primarily Office

Position: BI Engineering and Enablement Director (Primarily Office)
## BI Engineering and Enablement Director (Primarily Office)
Apply remote type:
On-site locations:
WI Madison:
MA Boston time type:
Full time posted on:
Posted Yesterday time left to apply:
End Date:
August 7, 2026 (16 days left to apply) job requisition :
R39132

This position provides strategic leadership for BI Engineering & Enablement, including BI tool administration, shared metrics enablement, semantic and knowledge-layer usage practices, metadata and lineage enablement, data layer usage governance, and AI-ready analytics foundations. You will ensure enterprise users, analytical tooling, dashboards, and AI-enabled workflows operate from consistent, governed, and explainable business definitions.
You will partner across business, Data Engineering, Governance, Applied AI, AI Platform Engineering, Enterprise Architecture, Information Security, Application Development, Digital Services, Infrastructure, and business operations teams to improve trust, adoption, and reuse of enterprise analytics capabilities. Metric layer, semantic layer, knowledge layer, metadata, and lineage capabilities are shared responsibilities with Data Engineering and Governance, with BI Engineering & Enablement leading enablement, adoption, BI consumption patterns, metric/semantic usage practices, and AI-consumable context.

You will also coordinates BI and analytics platform partners such as Tableau and GCP.Position Compensation Range:$ - $Pay Rate Type:

Salary
* Compensation may vary based on the job level and your geographic work location.
* * Relocation support is offered for eligible candidates.
*** Primary Accountabilities**
* ** Lead shared metrics enablement and adoption**  + You will lead enterprise practices for promoting adoption and consistent use of shared metrics in partnership with Data Engineering, Governance, and business owners.  + You will establish metric-layer usage expectations for grain, definitions, dimensions, ownership, reuse, and change management in partnership with the teams that own upstream data engineering and governance practices.
* ** Enable AI-consumable BI and semantic foundations**  + You will build and govern BI foundations that can be consumed by both humans and AI systems, including metric definitions, semantic context, metadata, lineage, classification, and knowledge catalog capabilities in partnership with Data Engineering and Governance.  + You will ensure agents and AI-enabled workflows can retrieve trusted business context from governed sources.
* ** Lead BI tool administration and best practices**  + You will oversee BI and analytical tool administration, standards, enablement, and adoption practices.  + You will support tool consolidation and rationalization.  + Promote consistent and effective use of BI capabilities across business and technology teams.
* ** Enable semantic and knowledge-layer usage**  + You will lead enablement and usage practices for semantic, metric, and knowledge-layer foundations that connect data assets to business meaning.  + Partner with Data Engineering and Governance on stewardship, upstream ownership, lineage, metadata, and governance practices.  + You will enable consistent business logic for dashboards, self-service analytics, embedded analytics, copilots, and AI-enabled workflows.
* ** Govern data layer usage for BI and analytics**  + Establish governance practices for how curated data layers, metric layers, semantic layers, knowledge layers, and BI assets are used.  + You will reduce metric drift, definitional inconsistency, duplicative reporting logic, and fragmented analytics experiences.
* ** Advance AI-ready analytics foundations**  + Structure BI, metrics, semantic context, metadata, lineage, knowledge assets, and business definitions so they can support both human decision-making and AI-powered tooling.  + You will partner with Applied AI and AI Platform Engineering to ensure AI systems use trusted definitions and explainable business context.
* ** Assess business and Technology readiness**  + Help assess readiness for AI-enabled analytics and decision intelligence, including data availability, data quality, data classification, metadata completeness, lineage visibility, process context, and business definition maturity.  + Identify gaps that could limit trusted BI, self-service analytics, or AI-enabled workflows.
* ** Manage BI and analytics platform partnerships**  + You will coordinate BI and analytics platform partner relationships relevant to the role, including Tableau and GCP.  + Ensure partner capabilities are aligned to enterprise BI, metric, semantic, governance, and AI-ready analytics expectations.
* ** Drive business enablement and adoption**  + Drive adoption of shared metrics, BI best practices, and trusted analytics patterns.  + Help business partners understand and use governed metrics and BI capabilities effectively.
* ** Lead people and develop talent**  + Lead teams responsible for BI enablement, BI engineering, metric-layer enablement, tool consolidation,…