Senior Data Analyst - Business Insights & Operations
About the Role
We're hiring a Senior Data Analyst to be the connective tissue between our data and every decision the company makes. Today, Finance and Revenue Operations each run their own reports, but those systems sync on a limited, manual cadence, and no one owns the full picture: Product and Leadership lack visibility into how the platform is actually being used, revenue reporting is fragmented across tools, and customer usage and health data is inconsistent and hard to trust.
This person will operationalize our data end-to-end, building the pipelines, dashboards, and automated reporting that let every function, including Product, Engineering, Data Engineering, Revenue, Finance, Customer Success, Operations, Support, GTM, and Leadership, see clearly and act quickly. This is not a role that duplicates the reporting Finance and Revenue Operations already own; it's the role that connects their outputs to everyone else, fills the gaps between systems, and builds the shared source of truth the company is missing. You'll report directly to our COO and partner with every function in the business, including Data Engineering on the systems and tooling that make reporting possible in the first place.
As a remote-first company, we welcome applicants based anywhere in the United States or Canada. You will join a high-ownership, high-trust engineering culture where self-starters thrive, ruthless prioritization is celebrated, and autonomy is the natural state of work. We move quickly, operate transparently, and expect every team member to think strategically, execute pragmatically, and elevate the people around them.
At Spinwheel , our mission is bold: we're building the infrastructure that powers intelligent debt management and financial empowerment. Our platform helps consumers understand, manage, and eliminate debt faster, powered by real-time credit data, optimization engines, AI-driven workflows, and modern financial APIs. Following our recent Series A, we're scaling rapidly and investing deeply in the data, reporting, and analytics infrastructure that lets us understand and run the business as well as we run the platform itself.
A key differentiator for this role: you will use AI tools and agents, including Claude, as a core part of how you work, automating recurring analysis, building lightweight agents that answer business questions on demand, and scaling reporting without scaling headcount.
Key Responsibilities
Building the Company's Shared Source of Truth
- Design and maintain unified reporting that pulls from multiple systems (CRM, Accounting, Invoicing, Operational DBs, etc.) for one consistent, trusted view.
- Replace ad hoc, manually-synced exports with reliable, more real-time data pipelines and refresh cadences.
- Define and document shared metric definitions (e.g., MRR, activation, churn) so every function reports the same numbers the same way.
Data Engineering Partnership & Stack Strategy
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Work closely with Data Engineering on the architecture, reliability, and scalability of the pipelines feeding Redshift and MongoDB Atlas, flagging gaps that affect reporting quality or freshness.
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Serve as a key voice in evaluating and selecting BI and analytics tooling, including assessing whether our current tool, ThoughtSpot, still meets the business's needs as we scale, and helping lead a transition if a change is warranted.
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Represent the reporting and analytics perspective in broader data stack decisions, including warehouse, ELT/ETL, data catalog, and governance, so tooling choices serve the people using the data, not just the people moving it.
Revenue & Financial Visibility
This complements, not replaces, the revenue and pipeline reporting Finance and Revenue Operations already own. The goal is to make their numbers visible, consistent, and easy to act on everywhere else in the business.
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Partner with Finance to extend revenue reporting (MRR/ARR bridge, new vs. expansion vs. churned revenue, revenu