Business Intelligence Analyst

The Business Intelligence Analyst (BIA) supports the Strategy & Analytics department by combining strategy, business intelligence, advanced analytics, data management, and operational support, serving as a high-impact analytical consultant to the Marketing department and leaders throughout the organization.

This role serves as a bridge between marketing strategy, data engineering, analytics, and sales. The ideal candidate will take ownership of transforming raw marketing, audience, and transactional data into building robust dashboards, and measuring the ROI of our marketing initiatives. They will further provide comprehensive data analysis for decision support, develop models to identify trends, patterns, and opportunities for business improvement, and continuously innovate to help us stay competitive with longer-term business initiatives.

The ideal candidate pairs a strong analytical mindset with excellent communication skills, a proven ability to collaborate across teams, and a passion for using data to drive engagement and revenue.

• BI & Dashboard Development: Design, build, and maintain automated, scalable dashboards and reports to track key performance indicators (KPIs) such as CAC, LTV, ROI, and conversion rates.
• Campaign Performance & Analytics: Analyze the performance of multi-channel marketing campaigns (paid media, email, organic, web)
• Data Pipelines & Modeling: Partner with the data engineering team to ensure marketing data from various source systems (CRMs, ad platforms, web analytics) is accurately ingested, cleaned, and modeled for reporting.
• Ad-Hoc Analysis: Conduct exploratory data analysis to answer critical business questions from executive leadership and stakeholders.

• Data Querying & Manipulation: Strong proficiency in SQL (writing complex queries, joins, and aggregations) to extract and manipulate data from cloud data warehouses.
• Data Visualization: Proven experience building clean, intuitive, and stakeholder-ready dashboards using modern BI tools.
• Data Modeling Concepts: Familiarity with relational databases, data warehousing concepts (e.g., star schemas), and how marketing data structures align.
• Statistical Basics: Understanding of A/B testing methodologies, statistical significance, and basic forecasting techniques.
• Analytical Curiosity: A natural urge to dig deeper into the "why" behind the data, rather than just reporting the "what".
• Attention to Detail: High commitment to data integrity, validating reports thoroughly before presenting findings.
• Team Player
  :
  Self-starter passionate about helping lead the team toward advancing the business. Champion innovative ways to find growth by working within the team environment. Align with team to adopt and develop best practices.

• 2-4 years of experience in business intelligence, data science, or other highly analytical role. Experience with in sports, entertainment, or a high-growth tech environment is preferred.
• Technical Stack includes, but not limited to:
• Advanced SQL - ability to write complex, performant queries and manage data transformations. Uses, but does not rely solely on, AI tools to improve efficiency.
• Marketing & Web Analytics
  :
  Google Analytics 4 (GA4) Adobe Analytics, and Google Tag manager (GTM).
• Marketing Platforms
  :
  Google Ads, Meta Ads Manager, Hub Spot, Salesforce, SFMC, or Marketo.
• Data Visualization
  :
  Advanced capabilities in Power BI, Tableau, or Looker.
• Optional/Plus
  :
  Basic Python or R for data manipulation and modeling.
• Strong ability to solve problems and deal with ambiguity. Hypotheses driven and able to logically break down approach and assumptions.
• Team player, proactive, results-oriented, strategic thinker, highly organized,…