Business Intelligence Analyst
Indexed description
At National Fitness Partners, we don’t just work in fitness— we TRANSFORM LIVES through affordable fitness. As the largest Planet Fitness franchise, we serve over one million members across 200+ clubs nationwide, creating a Judgement Free fitness experience.
- We Are Accountable – Self-starters who pursue excellence.
- We Are Driven – Problem solvers who deliver results.
- We Are Passionate – Positive energy with a real desire to help others.
- We Are Ambitious – Always learning and growing toward success.
Benefits
- Growth Opportunities over 90% of our management team started as an entry level team member!
- PTO for all employees
- 401K Retirement Fund (Employer match up to 4%!)
- Health Insurance Options including Health, Dental, Vision, family life insurance, and more
- Basic Life Insurance & Short-Term Disability I00% Company Paid!
- Employee Assistance Program
- Free employee Black Card Membership
This position serves as both a technical analytics resource and a cross-functional business partner, working closely with Finance, Operations, HR, Marketing, IT, and senior leadership to translate complex business questions into reliable data solutions. The BI Analyst will gather requirements, define and standardize key performance indicators, build and maintain data pipelines and reporting structures, validate data accuracy, and present insights in a clear, practical, and business-oriented manner. Success in this role requires strong technical capability in SQL, Python, BI tools, and cloud-based data platforms, combined with curiosity, sound business judgment, and the ability to communicate effectively with both technical and non-technical audiences.
Essential Job Functions
Business Intelligence, Reporting & Dashboard Development
- Design, build, and maintain interactive dashboards, visualizations, and self-service reporting tools using Sigma, Power BI, , or similar platforms.
- Translate raw data from accounting, financial systems, operations, HR, marketing, and other business areas into clear, accurate, and actionable reporting outputs.
- Develop recurring and ad hoc reports that communicate KPIs, trends, variance analysis, performance drivers, and business implications.
- Design, build, and maintain scalable ETL/ELT data pipelines using SQL, Python, PySpark, cloud-based orchestration tools, APIs, databases, flat files, and third-party platforms.
- Build and maintain data models, schemas, semantic layers, and warehouse structures, including dimensional models, to support consistent and scalable reporting and analytics.
- Write and optimize complex SQL queries, tune data workflows, and improve data storage, retrieval, processing performance, and reliability across reporting environments.
- Support forecasting, segmentation, optimization, experimentation, and data science initiatives by preparing reliable datasets, curated inputs, and scalable data assets.
- Evaluate and apply AI-enabled analytics tools, including generative AI and large language models, to improve reporting automation, data exploration, insight generation, and business productivity.
- Use AI and LLM-enabled tools responsibly by following appropriate data privacy, security, governance, validation, and documentation standards.
- Partner with leaders and stakeholders across Finance, Operations, HR, Marketing, IT, analytics, and senior leadership to understand business needs, define reporting requirements, and align data initiatives with organizational priorities.
- Define and standardize key performance indicators, support budgeting, forecasting, and financial performance analysis, and identify opportunities for cost optimization, revenue growth, and operational efficiency.
- Ensure data integrity, consistency, security, and compliance by implementing validation checks, access controls, monitoring, documentation, and governance standards.
- Perform data validation, cleansing, reconciliation, and root-cause analysis to resolve data discrepancies, reporting issues, and process gaps.
- Automate manual reporting processes, improve data workflows, document business logic and reporting standards, and stay current with BI, analytics, AI, and data engineering technologies.
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