Data Engineer Senior Consultant

Allstate is an insurance company focused on protecting families and their belongings from life’s uncertainties. The Data Engineer Senior Consultant will own the design, development, maintenance, and architecture of a Microsoft Fabric marketing semantic layer, including data pipelines, models, DAX measures, documentation, data quality, and performance. The role also partners with data engineering and business intelligence teams, investigates model issues, mentors apprentice team members, and contributes to applied AI efforts.

Responsibilities:

• Design, develop, and maintain the data pipelines and backend queries that populate the semantic layer, maintaining separation between raw, clean, and reporting layers so business logic lives where it belongs and not in the reporting layer
• Own the data modeling and architecture of the semantic layer end to end: structure, relationships, storage mode, and refresh behavior, including the architectural decisions behind each
• Author, maintain, and performance-tune the DAX measure layer, including the measure patterns downstream report builders depend on
• Implement and maintain data frameworks and architectures that keep the platform's data consistent, accurate, and ready for use
• Produce and maintain model documentation as a first-class deliverable, since the semantic layer serves report builders, analysts, and stakeholders who did not build it
• Combine, optimize, and manage multiple upstream data sources, partnering with the business intelligence and data engineering teams on source changes, deployment practices, and promotion of work from development into production
• Serve as the technical point of contact when downstream consumers report the model is wrong, and own the investigation through to root cause and fix
• Perform on-demand analysis of complex data to identify strategic opportunities and efficiencies and to keep key business metrics accurate and trustworthy
• Mentor apprentice team members working on model quality assurance and report migration, and review their work
• Contribute to the department's applied AI efforts, including agent-based access to model documentation and semantic models

Requirements:

• Strong SQL, including T-SQL, sufficient to write, review, and debug production analytical queries, and to recognize when generated or inherited code is incorrect rather than merely plausible
• Python, sufficient to build and maintain data transformation notebooks
• DAX, including measure authoring, performance tuning, and evaluation context
• Demonstrated experience owning a large, centralized semantic model or semantic layer, or an equivalent analytical data product, including responsibility for its structure rather than only its contents
• Experience working with data engineering and business intelligence partners on shared infrastructure
• Ability to make and defend architectural decisions independently, and to explain the tradeoffs to both technical and business audiences
• Microsoft Fabric experience (pipelines, lakehouses, warehouse, Direct Lake semantic models). Fabric experience is rare and learnable on the job by a strong candidate, so this is preferred rather than required
• Tabular Editor
• Marketing measurement or attribution background: how spend connects to quotes, binds, policies, and lifetime value
• Insurance industry experience
• Experience building or operating data quality frameworks
• 3 or more years of experience (Preferred)