Data Analyst (Finance)

• →Remote First Work Environment (US Based)

• →Medical, Dental, Vision

• →401K, 401K Match

• →Life and Disability Benefits

• →Unaccrued Paid Time Off

• →11 Paid Holidays

• →Employee Discounts

• →Employee Assistance Program

• →Educational Assistance Program

• →Employee Referral Program

• →Paid Parental Leave

The Finance Data Analyst will serve as the primary analytical and data-process partner from the data team to the Finance team, ensuring that financial data from Mission's enterprise data warehouse (EDW) is accurate, complete, timely, and usable for accounting, reporting, and ad hoc analysis. This role will assume day-to-day responsibility for the existing finance ETL process while it remains in use, compare EDW output with this process, investigate and explain differences, and establish repeatable validations for premium, commissions, taxes, fees, payments, and other policy transaction data.

The ideal candidate combines insurance accounting knowledge with strong SQL and data analysis skills, sound judgment about whether financial results make sense, and the ability to translate Finance requirements into reliable data processes.

• Assume day-to-day responsibility for running, monitoring, and troubleshooting the existing daily finance ETL accounting process while it remains in use, producing policy transactions and monetary amounts across premium, taxes, and fees.
• Compare financial data produced by the EDW with the current finance ETL outputs; reconcile results at the appropriate policy, transaction, coverage, or other business grain.
• Investigate variances and pinpoint root causes such as missing or duplicated transactions, timing differences, incorrect signs, mappings, joins, effective dates, transformation logic, or source-data defects.
• Use significant SQL to query, validate, and transform policy, premium, commission, payment, tax, fee, and related financial data; develop reusable queries and process components.
• Establish, document, and maintain automated validation rules, reconciliation checks, reasonableness tests, and exception reporting for financial data delivered from the EDW.
• Provide Finance with accurate and timely recurring data, reports, reconciliations, and supporting schedules for accounting, reporting, close, and operational needs.
• Work closely with Finance as the primary business stakeholder to define financial metrics, transaction treatments, data definitions, accounting assumptions, and acceptance criteria for EDW outputs.
• Partner with data engineers to trace source-to-target logic, recommend field-level changes, validate fixes, and support reliable production processes.
• Build a strong working knowledge of the EDW data model, including the insurance policy lifecycle, transaction data, source systems, data layers, grains, and relationships needed for financial reporting.
• Help define how paid data is sourced, ingested, modeled, validated, and made available in the EDW, including required history, timing, grain, and financial attributes.
• Support portfolio / program health check reporting through data preparation, KPI reporting, and process improvements.
• Perform ad hoc analyses for Finance; quantify business impacts, explain trends, and translate findings into clear takeaways.
• Create process flows, SQL documentation, data dictionaries, reconciliation procedures, and issue logs to promote repeatability and shared understanding.

• 4+ years of experience in finance data analysis, financial reporting, accounting analytics, business intelligence, or related analytical roles.
• 2+ years of experience working with commercial or specialty insurance, including policy, premium, commission, paid, tax, fee, or other transaction data.
• Working knowledge of insurance concepts, including premium and commission transactions, taxes, fees, and reconciliations.
• Strong SQL skills, including complex joins and aggregations, financial reconciliations, data validation, and development of reusable queries or processes.
• Experience comparing data across systems or ETL processes and diagnosing the root causes of discrepancies.
• Experience building or maintaining recurring reports, validation checks, or financial data controls using SQL, Excel, BI, or similar tools.
• Strong critical thinking, attention to detail, communication, and documentation skills, with the ability to explain technical issues and financial results to Finance and Data stakeholders.

• Experience supporting financial processes, planning, management reporting, or process automation.
• Experience with enterprise data warehouses, relational or dimensional data models, or data pipeline development.
• Familiarity with Databricks, PySpark, Python, Azure, or similar data engineering and development tools.
• Experience with Power BI or other BI tools, and with ERP, general ledger, premium accounting, policy administration, or billing systems.
• Bachelor's degree in finance, accounting, economics, data analytics, information systems, or a related field, or equivalent experience; ability to travel up to 5% of the year.

• Familiarity with insurance financial data domains, including policy transactions, premium, commission, paid data, taxes, fees, reconciliations, and downstream accounting or reporting.
• Ability to evaluate financial results using business context, recognize unexpected patterns, distinguish expected timing or business differences from data defects, and assess materiality.
• Strong relational database and data warehousing knowledge; able to use SQL effectively across normalized and denormalized schemas and multiple data grains.
• Skilled in reconciliation, variance analysis, root cause analysis, and the design of validation checks, reasonableness tests, and exception reporting.
• Proficiency in Excel to prepare recurring Finance reporting and support one-off analysis.
• Comfortable collaborating with data engineers and business users to trace data flows, clarify assumptions, troubleshoot processes, and drive issues to resolution.
• Able to document queries, financial definitions, accounting assumptions, reconciliation logic, process flows, and data-quality decisions for shared understanding.
• Detail-oriented, organized, and dependable when working with daily processes, recurring financial deliverables, and sensitive monetary data.

• Requires a quiet work environment with regular sitting at a computer for extended periods of time.
• Occasional walking and standing, and lifting of up to 10 lbs.
• Regular use of hands and fingers.
• Frequent talking or hearing.
• Vision requirements: Close, distance, color, peripheral, focus and depth perception.