Overview Join Casey's Analytics Solutions team as an Insights Analyst, where you'll design, build, and operate enterprise-grade semantic models and Power BI solutions that power trusted insights across the organization. This role sits at the intersection of data engineering, analytics, and BI platform development. Rather than focusing on ad-hoc analysis, the Insights Analyst is responsible for building scalable, high-performance Power BI semantic models, optimizing refresh and query performance, and enabling self-service analytics at scale. You'll partner closely with Data Engineering, business stakeholders, and analytics consumers to turn complex data into durable analytical products using best-in-class Power BI modeling, DAX, and platform practices.
Based upon experience open to hiring at the Senior Insights Analyst level.
Key Responsibilities: - Design, build, and maintain enterprise-grade Power BI semantic models that serve as trusted analytical foundations across multiple business units.
- Contribute to data modeling strategy for analytics use cases, including dimensional modeling, star schemas, and business metric standardization.
- Develop and optimize DAX measures, calculation groups, and model relationships with a focus on performance, maintainability, and semantic clarity.
- Implement and tune incremental refresh, partitions, aggregations, and query optimization to support large-scale datasets and enterprise workloads.
- Partner with Data Engineering to ensure upstream data models are optimized for analytical consumption and Power BI performance.
- Establish and enforce Power BI best practices across modeling, naming conventions, security (RLS), and dataset lifecycle management.
- Support self-service analytics by delivering well-documented, governed semantic models that minimize reporting complexity.
- Build and scale the enterprise analytics workforce through training, certification programs, technical communities, knowledge sharing, standards, and best practices.
- Provide oversight and consulting recommendations to Power BI-enabled Analysts within business unit analytics functions.
Compensation: Starting pay range: $81,500 - $112,100. Actual pay may vary based on Casey's assessment of the candidate's knowledge, skills, abilities (KSAs), related experience, education, and qualifications. Other factors impacting pay include local prevailing wages and internal equity. This position is eligible for an annual cash bonus based on company performance. Our full salary range for this role does extend beyond the hiring range listed, allowing team members the opportunity to continue to grow within the company.
Requirements - This position requires authorization to work in the U.S. without the need for employment-based immigration sponsorship now or in the future. Casey's will not provide sponsorship or employer support for applications or petitions for F-1 OPT, F-1 CPT, H-1B, L-1, TN, O-1, E-3, H-1B1, J-1, or any other employment-based visa.
- Bachelor's degree in Computer Science, Analytics, Engineering, Information Technology, or equivalent years of related work experience.
- 3-5 years of experience in analytics engineering, BI engineering, or semantic data modeling.
- Advanced Power BI expertise, with deep experience in:
- Semantic model design
- DAX (including performance tuning)
- Power Query (M)
- Row-level security (RLS)
- Strong foundation in dimensional modeling (facts, dimensions, star schemas).
- Proven experience optimizing Power BI performance, including query plans and refresh strategies.
- Proficiency with SQL and working with analytical data platforms.
This role
does not allow for 100% remote work. Qualified candidates must live within a daily commutable distance of Casey's Store Support Center in Ankeny, IA and be willing to work
onsite 5 days per week.
Preferred Technical Experience: - Experience with Power BI companion tools such as Tabular Editor, DAX Studio, and ALM Toolkit.
- Familiarity with source control and deployment pipelines for BI assets (Azure DevOps, GitHub).
- Experience working with cloud data platforms and lake house architectures (Databricks strongly preferred; Snowflake or BigQuery acceptable).
- Understanding of CI/CD patterns and environment promotion for semantic models.
- Exposure to large datasets and enterprise BI governance practices.
