Data Analyst (Finance)

Mission US

1d•Remote

About The Position

The Finance Data Analyst serves as the primary analytical and data-process partner between the data team and Finance. The role ensures financial data from Mission's enterprise data warehouse (EDW) is accurate, complete, timely, and usable for accounting, reporting, and ad hoc analysis. It assumes day-to-day responsibility for the existing finance ETL process while it remains in use, compares EDW output with that process, investigates differences, and establishes repeatable validations for premium, commissions, taxes, fees, payments, and other policy transaction data. The role combines insurance accounting knowledge with strong SQL and data analysis skills, sound judgment about financial results, and the ability to translate Finance requirements into reliable data processes. It works closely with Finance as the primary business stakeholder and partners with data engineers to improve and validate EDW processes. This is a remote position; planned in-office activities may occasionally be required, typically 2–4 times per year. The employee must live in the United States and be authorized to work there without employment sponsorship or a visa.

Requirements

At least 4 years of experience in finance data analysis, financial reporting, accounting analytics, business intelligence, or related analytical roles.
At least 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 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, including the ability to explain technical issues and financial results to Finance and Data stakeholders.
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, with the ability to use SQL effectively across normalized and denormalized schemas and multiple data grains.
Skill in reconciliation, variance analysis, root-cause analysis, and designing validation checks, reasonableness tests, and exception reporting.
Proficiency in Excel to prepare recurring Finance reporting and support one-off analysis.
Ability to collaborate with data engineers and business users to trace data flows, clarify assumptions, troubleshoot processes, and drive issues to resolution.
Ability to document queries, financial definitions, accounting assumptions, reconciliation logic, process flows, and data-quality decisions.
Detail-oriented, organized, and dependable when working with daily processes, recurring financial deliverables, and sensitive monetary data.
Quiet work environment with regular sitting at a computer for extended periods; occasional walking and standing, lifting up to 10 lbs, regular use of hands and fingers, and frequent talking or hearing.
Must live in the United States and be authorized to work in the United States without employment sponsorship or a visa.

Nice To Haves

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.

Responsibilities

Run, monitor, and troubleshoot the existing daily finance ETL accounting process while it remains in use, producing policy transactions and monetary amounts across premium, taxes, and fees.
Compare EDW financial data with current finance ETL outputs and reconcile results at the appropriate policy, transaction, coverage, or other business grain.
Investigate variances and identify root causes, including missing or duplicated transactions, timing differences, incorrect signs, mappings, joins, effective dates, transformation logic, or source-data defects.
Use 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 with Finance 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.
Develop working knowledge of the EDW data model, 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 and 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.