Senior Data Analyst

NationsBenefits is seeking a Senior Data Analyst to turn complex data into meaningful insights that drive product performance, program outcomes, operational effectiveness, and business decisions. The role partners with Product, Operations, Client Success, Analytics Engineering, Data Engineering, and business leadership to define metrics, analyze performance, investigate trends and root causes, and translate findings into actionable recommendations.

Responsibilities:

• Partner with Product Managers and business leaders to define KPIs, metrics, and measurement frameworks for products, programs, and strategic initiatives
• Analyze product performance, utilization, adoption, engagement, financial performance, and member behavior
• Conduct deep-dive analyses to identify trends, anomalies, opportunities, and key drivers of business performance
• Evaluate new product capabilities, program changes, and business initiatives using data-driven analytical approaches
• Develop ongoing measurement strategies to track product and program performance over time
• Help stakeholders understand what happened, why it happened, and what should happen next
• Write advanced SQL in Databricks to analyze large and complex datasets
• Combine data from multiple sources to develop comprehensive views of customers, members, products, and programs
• Perform exploratory analysis, segmentation, cohort analysis, trend analysis, variance analysis, and root-cause analysis
• Investigate unexpected changes and identify meaningful relationships and patterns within data
• Translate analytical findings into actionable business recommendations
• Solve complex and ambiguous business questions using structured, data-driven approaches
• Partner with Analytics Engineering and business stakeholders to establish consistent business metrics and analytical definitions
• Help develop standardized measurement approaches across products and programs
• Identify data quality, availability, and modeling issues that may impact analysis
• Work with Data Engineering and Analytics Engineering teams to improve underlying datasets and analytical models
• Validate analytical datasets and ensure metrics accurately represent business processes
• Contribute analytical and business requirements to reusable Gold-layer datasets and analytical data products
• Develop recurring analytical views and reporting that enable Product and business teams to monitor performance
• Support customer-facing reporting and analysis with accurate, explainable, and consistent metrics
• Help transition recurring analytical requests from one-off analysis into standardized and reusable solutions
• Present complex analytical findings through clear visualizations, presentations, and recommendations
• Support business reviews, product reviews, client discussions, and strategic planning
• Develop deep expertise in the products, programs, and business areas you support
• Serve as a trusted analytical partner to Product Managers and business leaders
• Help stakeholders define business questions and determine how data can inform decisions
• Proactively identify analytical opportunities rather than simply responding to requests
• Challenge assumptions and help distinguish between symptoms, root causes, and actionable opportunities
• Communicate findings clearly, including assumptions, limitations, and areas of uncertainty

Requirements:

• 5+ years of experience in data analytics, product analytics, business analytics, or a related field
• Advanced SQL skills and experience working with large, complex datasets
• Strong hands-on experience with Databricks or a comparable modern cloud data platform
• Demonstrated experience supporting product, program, or business performance analytics
• Strong understanding of analytical techniques including:
• Segmentation
• Cohort analysis
• Trend analysis
• Variance analysis
• Root-cause analysis
• Exploratory analysis
• Experience defining KPIs, metrics, and measurement frameworks
• Strong data validation and problem-solving skills
• Ability to translate ambiguous business questions into structured analytical approaches
• Excellent communication skills with the ability to present analytical findings to both technical and non-technical audiences
• Ability to collaborate effectively across Product, Engineering, Operations, Analytics, and business teams