Business Data Analyst

The Business Data Analyst uses data to uncover insights that enhance customer experience and drive operational excellence. This role bridges the gap between analytics and action, helping leaders understand what drives satisfaction, retention, and growth across our customer base. The ideal candidate brings hands-on technical expertise with SQL, Tableau, and Power BI, along with a passion for translating data into stories that improve how we serve our customers. You’ll work cross-functionally with teams in Customer Experience, Sales, Operations, and Finance to provide visibility into key business metrics and guide data-informed decision-making.

• Design, maintain, and enhance Tableau and Power BI dashboards that deliver insight into customer health, churn, NPS, and service performance.
• Use SQL to extract, join, and analyze data across multiple systems (Salesforce, customer feedback platforms, data warehouses).
• Partner with business stakeholders to define, track, and evolve key customer and operational KPIs.
• Conduct ad hoc analyses that inform CX strategy, operational improvements, and leadership initiatives.
• Develop and maintain data models and reporting structures to ensure accuracy, consistency, and repeatability.
• Collaborate with IT and Data Engineering to optimize data pipelines and automate recurring reports.
• Present clear, actionable insights to executives and non-technical teams—helping the business turn data into decisions.
• Contribute to a culture of data literacy within the Customer Experience organization.

• Strong SQL skills for querying and data manipulation (experience with views, stored procedures, and performance tuning).
• Proficiency in Tableau and/or Power BI, including dashboard design, data modeling, and interactivity (certifications preferred).
• Experience with Salesforce data and reporting; exposure to customer feedback systems (e.g. SurveyMonkey) or CS platforms (e.g. Gainsight) are a plus.
• Solid understanding of CX metrics—NPS, CSAT, churn, retention, and lifecycle analytics.
• Familiarity with ETL processes or data automation tools (Alteryx, Power Automate, Airflow, etc.).
• Excellent data storytelling and visualization abilities; able to communicate complex findings clearly and confidently.
• Knowledge of Python, R, or advanced Excel for data analysis is a plus but not required.