Sr. BI Engineer

Sr. BI Engineer | Dallas, TX | Hybrid | Direct Hire

A well-established, family-owned national food manufacturer is looking for a senior, hands-on BI Engineer to own the dimensional models its business depends on. You will sit directly with business partners, turn their reporting needs into well-designed star schemas, and write the T-SQL and pipelines yourself. There is no separate engineering team handing you finished structures. You will also build the semantic layer and the operational framework that keep the data trustworthy in production, while helping move legacy warehouse logic onto Azure SQL Managed Instance and Microsoft Fabric.

What You Will Do

• Design, build, document, and maintain the data warehouse architecture, including fact and dimension tables, star schemas, and source-to-target mappings
• Develop ETL/ELT routines that handle incremental loads, historical data, restartability, error handling, and load-order dependencies
• Build and maintain SSAS Tabular and Power BI semantic models, including measures, hierarchies, refresh orchestration, and row-level security
• Own warehouse reliability in production: monitor pipeline and cube processing runs, build audit, logging, and alerting frameworks, investigate failures, document root cause, and put fixes in place
• Integrate data from SQL Server, Azure SQL, Dataverse, Excel, SharePoint, APIs, and unstructured sources
• Migrate legacy SQL Server, SSIS, SSRS, and Tableau logic to Azure SQL Managed Instance and Microsoft Fabric
• Profile, validate, and reconcile data, and work with the relevant teams to resolve quality issues
• Partner with subject-matter experts, often in ambiguous situations, to define information and reporting requirements
• Keep technical documentation current (mappings, ETL specs, job dependencies, deployment notes) and take part in code review, source control, and release management within Scrum
• Provide technical and architectural guidance on reporting and analysis, and build strong relationships with technology and business teams

What You Bring

• 7+ years of hands-on data warehouse / BI engineering, having personally built these solutions rather than only directing others
• 5+ years designing and building Kimball dimensional models, with the ability to speak to grain, surrogate keys, slowly changing dimension types, and conformed dimensions from your own work
• 5+ years of advanced T-SQL: complex queries, stored procedures, views, functions, indexing, execution plan analysis, and tuning against large tables
• 4+ years building and deploying end-to-end ETL/ELT pipelines with SSIS, Azure Data Factory, Microsoft Fabric, or Synapse
• 3+ years supporting production data environments, including job monitoring, failure investigation, root cause documentation, and corrective action
• 2+ years with SSAS Tabular or Power BI semantic models, DAX measures, refresh orchestration, and row-level security
• Strong understanding of data warehouse architecture, data modeling, security, and usability principles
• Experience with source control and release management (Azure DevOps or Git), code review, and Scrum sprints
• Proven ability to gather requirements directly from business SMEs and translate them into a modeled, documented reporting solution
• Comfort with ambiguity and competing priorities in a fast-paced, collaborative team

Nice to Have

• Bachelor's degree in Computer Science, MIS, Data Engineering, IT, Engineering, or a related field (equivalent experience considered)
• Microsoft certification such as Fabric Analytics Engineer Associate, Azure Data Engineer Associate, or Azure Database Administrator Associate
• Microsoft Fabric, Azure Synapse, Azure Data Factory, Databricks, and/or SSIS (strength in the modern stack can offset lighter legacy experience, and vice versa)
• Azure SQL Database, Azure SQL Managed Instance, on-premises SQL Server, Azure DevOps, and Azure Data Lake
• CI/CD build and release pipelines and API-based data integrations
• Experience migrating a legacy warehouse (SQL Server, SSIS, Tableau) to a modern cloud platform
• Manufacturing data and knowledge of D365 Finance and Operations data structures

Work Schedule and Location

Hybrid, onsite Monday, Tuesday, and Thursday and remote Wednesday and Friday. Team or business needs may occasionally require additional onsite days. The office will change locations around 2027.