About the RoleWe're building an enterprise data platform on Microsoft Fabric to standardize how data is modeled, defined, and used across the organization. Today, key metrics are inconsistently defined, business logic is spread across multiple places, and trust in data varies by domain.
This role is central to fixing that.
As a Senior Analytics Engineer, you will design scalable data models, define canonical datasets, and own the semantic layer for a primary business domain. Your work will become the default source of truth for business logic and metrics, shaping how the organization measures performance and makes decisions.
This is not a pipeline-focused role. It sits at the intersection of data modeling, semantics, and platform design. You will operate in real ambiguity, where definitions may conflict and tradeoffs matter, and you will be expected to drive durable, aligned solutions across teams.
What You'll Do- Design scalable, reusable dimensional data models within your domain
- Define, standardize, and govern KPIs and business logic in a centralized semantic layer (Power BI / Fabric)
- Build canonical datasets and drive their adoption as the default source for reporting and analysis
- Own modeling decisions across structure, performance, cost, and maintainability
- Design cohesive solutions across Microsoft Fabric components (Lakehouse, Warehouse, Semantic Models)
- Lead alignment on definitions across stakeholders and ensure consistent implementation
- Identify and reduce sources of inconsistency, duplication, and low data trust, including pushing improvements upstream where feasible
- Establish lightweight governance guardrails (naming, conformed dimensions, measures, documentation) that enable consistent development
- Collaborate with the broader data team to evolve shared standards and platform patterns
- Apply AI tools thoughtfully to improve development speed and model quality, with awareness of limitations and risks
The EnvironmentYou'll operate in a maturing analytics environment where definitions, ownership, and trust vary by domain. This role helps provide structure and durability by consolidating logic into governed models, establishing canonical definitions, and introducing practical documentation and change control to prevent metric drift over time.
Qualifications- 6+ years in analytics engineering, BI engineering, or data modeling roles with end-to-end ownership of production data models
- Deep expertise in dimensional modeling (facts, dimensions, grain definition, conformed dimensions, SCDs)
- Hands-on ownership of a semantic layer (Power BI or equivalent), including reusable measures, relationships, and performance optimization
- Advanced SQL skills with experience building complex, performant transformations at scale
- Experience working across a modern analytics platform (storage, transformation, and semantic layers); Microsoft Fabric strongly preferred, with demonstrated ability to ramp quickly from an equivalent platform (Snowflake, Databricks, BigQuery)
- Proven ability to operate in ambiguous environments, resolve conflicting business definitions, and drive adoption of shared metrics
- Strong judgment in balancing tradeoffs across performance, usability, maintainability, cost, and governance
Preferred - Hands-on Microsoft Fabric experience
- Experience treating analytics assets as products (certification, adoption, documentation, change control)
What Makes This Role Different- You will build shared, governed data products-not one-off datasets
- You will own how business logic is defined and reused within your domain
- You will be measured by adoption, consistency, and durability, not output volume
- You will help shape standards in a platform that is still evolving
Why This Role MattersThe models, definitions, and standards you establish will directly shape how the business understands performance and makes decisions. This role is foundational to building a trusted, scalable analytics platform for the enterprise.
