Data Engineer with MS Fabric and Semantic Modeling

This role is essential for designing, building, and governing the enterprise semantic layer in Microsoft Fabric to enable trusted, self-service reporting and analytics across the business. It primarily involves partnering with data domain teams to assess and validate table readiness - data quality, grain, keys, and relationships - for semantic modeling, and providing clear recommendations on how source data from platforms like Snowflake and Databricks should be modeled for optimal semantic consumption. The role includes developing and optimizing the data pipelines that feed the semantic layer, as well as mentoring team members on semantic modeling and data engineering best practices. Success is measured by the adoption and reliability of semantic models, the readiness and quality of underlying data domains, and the team's growth in semantic modeling capability. The work impacts the organization by giving business users fast, trustworthy access to data and accelerating data-driven decision-making enterprise-wide.

What You'll Do

Design, build, and maintain semantic models in Microsoft Fabric (Power BI datasets, OneLake) to support enterprise reporting and self-service analytics.

Partner with data domain teams to assess table readiness for semantic modeling, evaluating data quality, grain, keys, and relationships, and communicating gaps back to source teams.

Provide recommendations on best-practice data modeling approaches (e.g., star schema, dimensional modeling, conformed dimensions) to optimize data for semantic layer consumption.

Develop and optimize data pipelines and transformations sourcing from Snowflake and/or Databricks into the semantic layer.

Perform data wrangling, exploration, and discovery of heterogeneous data to generate new business insights.

Mentor team members to build and enhance their semantic modeling and data engineering skillsets.

Assist management in project definition, including estimating, planning, and scoping semantic layer initiatives.

What You'll Bring

• 4-7 years | Building and maintaining semantic models using Microsoft Fabric, Power BI, or comparable BI/semantic modeling platforms
• 4-7 years | Working with cloud data platforms such as Snowflake and/or Databricks, including data readiness assessment and optimization for downstream modeling
• 4-7 years | Partnering with data domain/business teams to evaluate data quality, structure, and readiness, and translating findings into modeling recommendations
• 4-7 years | SQL and dimensional/relational data modeling design (e.g., star schema, snowflake schema, data vault)
• 4-7 years | Building complex data pipelines using languages such as SQL, DAX, Python, Java, Scala, and/or Go
• 3-5 years | Experience with cloud platforms (Azure, AWS, or Google Cloud)
• Microsoft Fabric or Power BI certification
• Experience with data governance, cataloging, or lineage tools Familiarity with monitoring/observability tooling (Prometheus, Grafana).
• Comfort operating in a forward-deployed, customer-facing technical role, owning solutions from prototype to production.

Education Level | Acceptable Equivalent Experience

• Bachelor's Degree | plus 5 years of related work experience OR Advanced degree with 3 years of related experience
• Acceptable areas of study include Computer Engineering, Computer Science, or a related subject area