StarRez is the global leader in student housing software, providing innovative solutions for on and off-campus housing management. As a Senior Business Intelligence Analyst, you will support the development and deployment of our data warehouse and BI software application, collaborating with cross-functional teams to create strategic insights and optimize our customer offerings.
Responsibilities:
- Design, develop, and maintain Domo dashboards, reports, and data visualizations to support business operations and strategic initiatives
- Assist in the design and implementation of the data warehouse architecture; ensuring data integrity and completeness and performance efficiency (via regular data validations and audits)
- Utilize Domo’s SQL, Magic ETL, and scripting tools to prepare data
- Collaborate with business leaders to gather technical requirements of complex data sets, assess trends/patterns, and convert them to actionable insights
- Lead dashboard rationalization efforts, consolidating or deprecating unused or duplicative content
- Contribute to BI training, enablement sessions, and best-practice documentation
- Support BI governance by reinforcing metric consistency, proper dataset usage, and business definitions
Requirements:
- 4+ years of proven experience in business intelligence, data analytics, or related fields
- Advanced proficiency in SQL for data extraction and manipulation
- Strong understanding of ETL processes and data warehousing principles
- Strong experience building dashboards and analytics in BI platforms (Domo preferred)
- Excellent problem-solving skills and ability to work with large datasets to draw meaningful insights from complex data
- Strong communication and storytelling skills to translate data into business insights with non-technical stakeholders
- Ability to manage multiple projects, prioritize tasks, and meet deadlines in a fast-paced SaaS environment
- Bachelor's Degree in Business Analytics, Data Science, Computer Science, Finance, or a related field
- Knowledge of Python, R, or JavaScript for advanced analytics
- Experience with data warehousing concepts and architecture
- Experience driving analytics adoption or self-service programs
- Familiarity with SaaS metrics (ARR, retention, usage, adoption)