Sr Finance Data Analyst

This is not a traditional Excel-based FP&A role. The data supporting pharmacy margin analysis is highly complex and requires significant manipulation, transformation, validation, and automation outside of Excel. The ideal candidate will have strong SQL coding experience, comfort working with large and complex datasets, and the ability to translate operational, reimbursement, procurement, and financial data into scalable analytics that can be used for executive reporting and business decision-making. The role will partner closely with Finance, Market Access, Margin Optimization, Pharmacy Procurement, IT/Data teams, and operations to ensure margin reporting is accurate, repeatable, and tied to financial results.

Responsibilities

• Builds, maintains, and enhances SQL-based data models supporting pharmacy margin analytics
• Develops backend logic to analyze profitability across drug, payer, channel, therapy, branch, claim, and patient-level dimensions
• Manipulates and transforms large, complex datasets outside of Excel using SQL and/or other coding languages
• Automates recurring margin reporting processes to reduce manual work and improve scalability
• Supports the development of rate, mix, volume, reimbursement, and unit cost bridges explaining gross profit performance
• Creates data pipelines, queries, and repeatable reporting logic for margin analytics and executive reporting
• Partners with the Finance Manager to translate business questions into structured data queries and analytical outputs
• Analyzes impacts from ASP, AWP, WAC, MAC, acquisition cost, reimbursement rate, payer mix, and drug utilization changes
• Integrates and validates data from multiple sources, including claims, revenue, COGS, drug cost, procurement, payer, branch, and financial systems
• Identifies and resolves data quality issues, mapping inconsistencies, duplicate records, missing values, and logic gaps
• Validates margin reporting outputs against financial statements, source system data, and operational reporting
• Supports claim-level and drug-level profitability analysis, including reimbursement accuracy and cost-to-claim mapping
• Partners with Margin Optimization to assess current claims, margin leakage, under-reimbursement, and payer-specific profitability trends
• Partners with Pharmacy Procurement to track drug cost changes, manufacturer rebates, wholesaler discounts, and purchasing trends
• Builds reporting datasets and dashboards in Power BI or similar visualization tools
• Documents query logic, data definitions, mapping assumptions, and reporting methodology
• Maintains strong controls around recurring reporting, including tie-outs, version control, and validation checks
• Supports ad hoc executive analysis related to pricing, payer strategy, reimbursement pressure, procurement savings, and margin improvement initiatives
• Translates technical findings into clear business insights for Finance and cross-functional partners

Qualifications

• 3–6+ years of experience in data analytics, business intelligence, financial systems, FP&A analytics, healthcare analytics, pharmacy analytics, or related field
• Significant SQL coding experience required
• Experience manipulating large and complex datasets outside of Excel required
• Experience with one or more additional tools/languages preferred: Python, R, Alteryx, Power Query, VBA, DAX, Power BI, Tableau, or similar analytics tools
• Healthcare, pharmacy, infusion pharmacy, specialty pharmacy, reimbursement, payer, or provider finance experience strongly preferred
• Understanding of pharmacy reimbursement concepts such as ASP, AWP, WAC, MAC, acquisition cost, payer reimbursement, and gross profit preferred
• Strong ability to build repeatable, scalable reporting logic and automate manual processes
• Experience working with transaction-level, claim-level, patient-level, or drug-level data preferred
• Strong data validation skills, including ability to reconcile reporting outputs to source systems and financial statements
• Advanced Excel skills required, but role should not be dependent on Excel as the primary data manipulation tool
• Experience with Power BI, SQL Server, Snowflake, Databricks, Alteryx, or similar database/reporting environments preferred
• Strong attention to detail and ability to identify data inconsistencies or logic errors
• Ability to work closely with Finance leaders to turn complex business questions into structured analytics
• Strong documentation skills, including query logic, data definitions, and reporting methodology
• Self-starter with strong problem-solving skills, intellectual curiosity, and ownership mentality
• Strong understanding of pharmacy reimbursement, payer dynamics, and infusion pharmacy margin drivers across PBM and Medical benefit channels
• Advanced financial modeling, variance analysis, and rate/mix/volume analytics skills
• Knowledge of pharmaceutical pricing methodologies including ASP, AWP, WAC, and MAC
• Ability to analyze large, complex datasets and translate findings into actionable business insights
• Expert-level SQL knowledge with extensive experience working in SQL Server environments, including relational database design, complex query development, performance tuning, stored procedures, views, functions, and SQL Server Agent jobs
• Familiarity with additional database platforms and data warehousing concepts is preferred
• Strong experience developing and maintaining automated data pipelines and ETL processes using SQL Server technologies, with the ability to optimize data workflows, troubleshoot failures, and ensure data integrity across enterprise systems
• Proficiency in data analysis and root cause investigation, with the ability to analyze large and complex datasets, identify data quality or process issues, and translate findings into actionable business insights
• Experience with reporting and data visualization tools such as Power BI or SSRS, including building dashboards, validating metrics, and supporting business users with analytical reporting needs
• Strong understanding of data governance, data validation, and reconciliation processes to ensure consistency and accuracy across internal and external data sources
• Ability to work collaboratively with business stakeholders, data engineers, and technical teams to gather requirements, document data flows, and support scalable analytical solutions