Senior Business Intelligence Engineer

Position Summary Daisy Brand is modernizing its data platform and data visualization strategy, moving from a traditional solution (SQL Server, SSIS, and Tableau) to a modern cloud data platform built on Azure SQL Managed Instance and Microsoft Fabric. We are looking for a Senior BI Engineer to help lead that transformation. Position Summary Daisy Brand is modernizing its data platform and data visualization strategy, moving from a traditional solution (SQL Server, SSIS, and Tableau) to a modern cloud data platform built on Azure SQL Managed Instance and Microsoft Fabric. We are looking for a Senior BI Engineer to help lead that transformation. In this role, you will design and build the dimensional models — the fact and dimension tables, star schemas, and the T‑SQL and ETL behind them — that the business runs on. You will translate business reporting needs into well‑architected, efficient data models, working directly with business partners rather than receiving finished structures from a separate engineering team. You will also build the semantic models and the operational framework that make those models trustworthy in production. This role will drive innovation, enhance user experience, and enable data democratization across our organization. This is a hands‑on engineering role. You will personally write the T‑SQL, build the pipelines, and own the results. Location and Travel Requirements This position operates under a hybrid work model, requiring onsite presence Monday, Tuesday, and Thursday, with Wednesday and Friday designated as remote workdays. While this schedule is typical, team or business needs may require additional onsite days. Corporate Office Location Update: Currently, the Daisy Brand corporate office is located in Dallas, TX at 635 and 75. Anticipated September 2027, we will be moving to the Granite Park business complex in North Plano (intersection of Dallas North Tollway and Sam Rayburn Tollway). Key Responsibilities Define, design, develop, document, and maintain dimensional data models and data warehouse architecture, personally building the fact and dimension tables, star schemas, and source‑to‑target mappings. Oversee and perform analysis, design, implementation, and support of the company data warehouse, including developing ETL/ELT routines with appropriate tools — handling incremental loads, historical data, restartability, error handling, and load‑order dependencies. Build and maintain semantic and analytical models (SSAS Tabular and Power BI semantic models), including measures, hierarchies, refresh orchestration, and row‑level security. Own production reliability for the data warehouse: monitor pipeline and cube processing runs, build audit, logging, and alerting frameworks, investigate failures, document root cause, and implement corrective action. Work across data sources such as SQL Server, Dataverse, Excel, Azure SQL, SharePoint, API‑based data, and unstructured data. Migrate legacy warehouse logic (SQL Server, SSIS, SSRS, Tableau) onto the modern Azure SQL Managed Instance and Microsoft Fabric platform. Maintain data integrity, ongoing solution quality, and adherence to security, architectural, and usability standards; perform data profiling, validation, and reconciliation, and resolve data quality issues with the relevant teams. Collaborate with subject‑matter experts, often in ambiguous situations, to determine business information and reporting requirements. Maintain technical documentation — source‑to‑target mappings, ETL specifications, job dependencies, and deployment notes — and participate in code review, source control, and release management within a Scrum process. Build and maintain relationships with technology teams and business partners to align technology initiatives with business strategy. Provide technical and architectural guidance to ensure effective reporting and analysis. Stay current on new technologies through continuous learning, industry publications, vendor contacts, and training. Other duties as assigned. Qualifications And Requirements Basic Qualifications 7+ years of hands‑on data warehouse / BI engineering experience — you have personally built these solutions, not only directed or coordinated others who did. 5+ years designing and building dimensional models using Kimball methodology, including fact and dimension tables, star schemas, and source‑to‑target mapping. You can explain 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, indexes, execution plan analysis, and query tuning against large tables. 4+ years building and deploying ETL/ELT pipelines end to end with SSIS, Azure Data Factory, Microsoft Fabric, or Synapse — including incremental loads, historical data handling, restart ability, error handling, and load‑order dependencies. 3+ years supporting production data environments: monitoring job runs, investigating failures, documenting root cause, and implementing corrective action. 2+ years with semantic and analytical models — SSAS Tabular, Power BI semantic models, DAX measures, refresh orchestration, and row‑level security. Thorough 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 working within Scrum sprints. Business‑facing communication — demonstrated ability to gather requirements directly from business SMEs in ambiguous situations and translate them into a modeled, documented reporting solution, communicating clearly with both business and technical partners. Comfort with ambiguity and competing objectives in a fast‑paced, collaborative, team‑oriented environment. Preferred Qualifications Bachelor’s degree in Computer Science, Management Information Systems, Data Engineering, Information Technology, Engineering, or a related field; equivalent professional experience will be considered in place of a degree. 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 experience in the legacy stack, and vice versa. Azure SQL Database, Azure SQL Managed Instance, on‑premises SQL Server, and Azure DevOps. Azure services including Azure Data Lake; CI/CD build and release pipelines; implementing API‑based data integrations. Experience migrating a legacy warehouse (SQL Server, SSIS, Tableau) to a modern cloud platform. Working with varied sources: SQL Server, Dataverse, Excel, Azure SQL, SharePoint Lists/Libraries, API‑based data, and unstructured data. Manufacturing data; knowledge of D365 Finance and Operations data structures. Company Overview Daisy Brand is the market leader in two billion‑dollar categories – sour cream and cottage cheese. Headquartered in Dallas, Texas, we’ve earned the trust of Americans through consistency and quality across five generations as a family‑owned company. Our success has been guided by a simple belief: good food, much like good work, starts with integrity. That mindset continues to shape how we make our products, run our business, and support the people behind the brand. At Daisy Brand, tradition and innovation go hand in hand. We invest thoughtfully in advancements that strengthen our products and operations, supporting responsible, long‑term growth. In 2025, we broke ground on a new manufacturing facility in Boone, Iowa, further strengthening our supply chain alongside our established plants in Garland, Texas; Casa Grande, Arizona; and Wooster, Ohio. Looking ahead, our state‑of‑the‑art Innovation Center, opening in 2026, will bring together research, food science, culinary, and technology teams to shape the future of our products. Recent work from these teams includes the development of the squeeze pouch and new line of dips, reflecting an intentional approach to modernization while staying true to the quality our consumers expect. At the heart of Daisy Brand is its people. The company is intentionally structured to be collaborative and accessible, with an entrepreneurial mindset encouraged at every level. We hire with the goal of building long‑term careers and provide an environment where employees are trusted to think critically, take initiative, and continue learning. Growth here isn’t accidental; it’s actively supported and shared. Benefits To support our employees and their families, Daisy Brand offers a people‑first benefits package that includes: A no deductible, $0 premium option for employee only medical coverage Access to virtual healthcare and wellness programs A 401(k) program with company match, plus weekly safe harbor and annual profit‑sharing contributions Company paid short and long‑term disability coverage and 2x annual salary in life and AD&D insurance Four weeks of paid time off, plus 20 hours of floating holidays in your first full year of employment Annual rollover and payout options for any unused paid time off Paid time for volunteering and community involvement Tuition reimbursement and ongoing professional development opportunities Fitness and wellness incentives And more. Daisy Brand is a nicotine‑free company. Daisy Brand is an Equal Opportunity Employer. Veterans and disabled encouraged to apply. #J-18808-Ljbffr Daisy Brand