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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Analyst, Finance - **Company:** Cedar Inc - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $99,500.0 - $130,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Software as a Service, Information Engineering, Payment Systems, Netsuite, SQL Databases, Scripting, Sql Optimization, Snowflake, Stripe, Tools for Reporting, Looker Analytics, Data Pipelines - **Published:** August 3, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=4e9d8889e31d9792 ## About the Role * 3-5 years in financial analytics, revenue operations, or billing operations in a SaaS or fintech environment * Advanced SQL and data querying skills (Snowflake preferred) * Experience with BI tools (Looker or Omni preferred) * Demonstrated ability to own end-to-end billing or reconciliation workflows * Strong cross-functional communication skills - able to translate between business and technical teams * Experience identifying and quantifying revenue leakage or billing discrepancies Preferred * Familiarity with NetSuite or similar ERP configuration * Experience with payment platforms (Stripe, PayPal, or similar) * Exposure to AI/ML tooling for workflow automation * Background working alongside Data Engineering in a transitioning ownership model * Healthcare or healthcare payments experience a plus ## Description This person will report to the Sr Manager, Billing & Revenue Accounting and work cross-functionally with Data Engineering and other key stakeholders. They will own the client billing data that Data Engineering historically held, freeing engineering to focus on platform and infrastructure. The desired outcome of this role is to allow for finance to: * Have a robust and efficient data pipelines that ensure data accuracy * Have a system in place that will support the scalability of the business * Have a system in place that could potentially connect to a new billing system in the future, * Transition billing operational tasks from Data Engineering to Finance, per the Client Billing Operating Model: * Own monthly reconciliations, with DE providing support only for technical defects * Lead billing investigations; escalate to DE only for system-level issues * Define and maintain payment attribution codes (business taxonomy, not engineering) * Determine bill eligibility per Finance policy * Monitor billing KPIs (credit memos, leakage, unbilled revenue, Stripe/PayPal/PayZen fees) * Serve as Finance's first line of response for client billing support questions * Conduct impact analyses of billing logic changes and communicate downstream effects to Finance leadership * Proactively identify discrepancies, fee calculation errors, and revenue gaps before they reach clients * Map data sources, identify inconsistencies, and support lightweight data governance practices * Build Finance reports leveraging the semantic layer maintained by Data Engineering * Finance Self-Service & AI-Enabled Tooling (30%) * Build and maintain BI dashboards and reports for Finance and cross-functional stakeholders * Automate manual Finance data tasks using SQL, Snowflake, and scripting * Train Finance team members on Looker, SQL, and reporting tools to reduce DE dependency * Champion AI tool adoption within Finance (e.g., payment attribution automation, anomaly detection) * Establish Looker standards and documentation to ensure consistent metric definitions * Revenue Integrity & Leakage Remediation (20%) * Audit billing filters to surface and quantify unbilled revenue across the client base * Reduce monthly leakage from pass-through costs through improved monitoring and root-cause analysis * Analyze and reduce credit memo frequency (52 issued in 2024, 54 in 2025) by identifying systemic overbilling causes * Partner with Revenue Lead to validate billing outputs and catch anomalies before month-end close * Support Billing 2.0 UAT to ensure data accuracy and operational readiness for the new system ## Related Videos - [Navigating Growth, Scaling Challenges, and Office Expansions with David Singleton, CTO at Stripe](https://www.wearedevelopers.com/videos/100362-navigating-growth-scaling-challenges-and-office-expansions-with-david-singleton-cto-at-stripe) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [JavaScript? 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