Senior Data Analyst, Strategic Operations

About Collective

Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self‑employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork.

Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, Tech Crunch, and more. We are backed by General Catalyst, Sound Ventures (Ashton Kutcher and Guy Oseary), QED Investors, Google’s Gradient Ventures, Expa, and other investors who have financed iconic companies like You Tube, Substack, Twitch, Box, Hims, Instacart, and Lyft.

You will own the architecture and buildout of Collective's Operations Intelligence Warehouse: the Big Query data layer and Metabase BI that make throughput, quality, variance, and capacity inspectable across an AI‑native financial operation. You will also own the analytics on top of it: spotting trends before they become problems, surfacing the signal leadership acts on, and seeing around corners with evidence rather than instinct.

The AI in an AI‑native financial services firm is only as good as the operation it learns from, and the operation is only as good as the data that describes it. That data layer is yours.

You will join Strategic Operations, the applied operations research team that designs how Collective's member delivery engine runs. Reporting to the Head of Strategic Operations, you will lead the design of our operational data, set the modeling and quality standards the team builds on, and turn raw production‑line telemetry into the operating metrics and insights the business runs on: cycle time, first‑pass yield, utilization, and cost‑to‑serve.

• Architect the Operations Intelligence Warehouse. Lead the audit, cleanup, and architecture of the Operations data subset within our shared Big Query warehouse: source‑of‑truth definitions, schema and dataset design, naming conventions, documentation, and query cost management.
• Set the data modeling standard. Build and maintain dimensional models in dbt with testing, lineage, and version control, so every operational metric traces to a governed, documented source.
• Instrument the operation. Design and maintain the dashboards and metrics that give leadership real‑time visibility into operational health: throughput per workflow, cycle time, first‑pass yield, exception rates, and capacity versus demand.
• Connect operations to revenue. Join operational data to GTM and financial data to answer the questions that matter: how service quality drives retention and NRR, what each workflow costs to run, and where margin is made or lost in the member delivery pipeline.
• Power statistical rigor. Partner with the team on statistical process control, variance analysis, and root cause analytics, replacing anecdote with evidence in daily operating decisions.
• Raise the data practice. Partner with our Data Engineering team, who own the company‑wide warehouse and pipelines, to establish the SQL, modeling, and analytics engineering standards Strategic Operations scales on.

• Experience: 5+ years in data analysis or analytics engineering at a B2B SaaS or fintech company, ideally one with a human‑in‑the‑loop service delivery operation.
• Analytical Powerhouse: Expert‑level SQL and hands‑on experience with dbt (data build tool), or equivalent, in a modern warehouse, Big Query and Metabase strongly preferred.
• Warehouse Wrangler: A track record of leading a data cleanup or warehouse re‑architecture: you have untangled inconsistent schemas, established sources of truth, and made a messy warehouse trustworthy.
• Quality‑First: Strong data quality instincts: testing frameworks, lineage, documentation, and git‑based workflows are how you work, not an afterthought.
• Signal from Ambiguity: Proven ability to take ambiguous operational questions and turn them into structured, measurable analyses that change decisions.
• Cross‑Fu…