Senior Analytics Engineer

About the role

As a Senior Analytics Engineer at Range, you'll own the single source of truth that the business runs on. Every key metric that drives the business will come from the layer that you own. We've grown quickly and organically over the past few years, and metric definitions have diverged along the way. There are different versions of the same number floating around the company, and a lot of time gets wasted reconciling them. You'll be the person who fixes that. This role is ideal for someone willing to dig deep with the business: to herd the cats, get the right people in the room, and pin down what we actually mean by a metric. It's also for someone with deep technical chops who writes tests for the most complex business logic, and who digs into the data like a detective when the numbers don't add up. You'll work closely with our Senior Data Engineer, who owns the foundational data model and ingestion layer, and our Head of Data and Analytics, who's setting the strategy. Together you're the foundation of Range's data team. We're excited to hire this role at Range's Headquarters in McLean, VA. All of our positions follow an in-office schedule Monday through Friday, allowing you to collaborate directly with your team. If you're not currently based in the area, but love what you see, let's discuss relocation as part of your journey to joining us. What you'll do with us Own the mart layer. Define the dimensional models, fact tables, and metrics that serve as Range's single source of truth. Make the calls on grain, naming conventions, and how business logic gets encoded in dbt. Get alignment on what we measure. Partner with business leaders across retention, sales, marketing, planning, and finance to define key KPIs and get sign-off on the definitions. Document them so nobody has to ask "is this the right number" again. Build for trust. Implement business-logic tests in dbt, freshness alerting, and the documentation that lets stakeholders use the data without having to ask you what it means. Build the dashboards the whole company runs on. Own the small set of certified dashboards that drive OKRs, board reviews, and exec decisions in Sigma. Make sure they match the mart layer exactly so the numbers don't drift. Set the conventions that distinguish "certified" from "exploratory" so business users know what to trust. Activate data where the business works. Build the operational data pipelines that get trusted data into the tools members and the business touch: Loops, Outreach, Salesforce, the application. We're open on tooling (Hightouch, Census, or a continued lightweight DIY approach); your judgment on what fits Range's scale and budget will help shape the call. Architect for governance in the mart layer and the dashboards built on top of it. Make sure PII classifications, access controls, and audit trails set at the source propagate cleanly through dbt and into BI tooling, including dashboard-level access controls and the row-level security that lets, for example, a planner see only their own clients. The business should be able to use data responsibly by default.

Requirements

• 5+ years of experience in analytics engineering, data engineering, or a hybrid role, including time owning a mart layer end-to-end.
• Production experience with a modern data toolset including dbt, a cloud warehouse or lakehouse, and modern orchestration tooling (we use Fivetran and GitHub Actions, but comparable experience is fine).
• Track record of partnering directly with business leaders to define metrics and get sign-off on definitions, not just executing on someone else's spec.
• What will set you apart
• You've owned data activation end-to-end. Built reverse ETL pipelines that business teams actually depend on, with the testing and monitoring discipline that prevents the kind of mistakes that affect customers.
• You leverage AI as a force multiplier in your own work. You've developed real instincts for when to lean on it, when to verify, and where it actually accelerates modeling, metric definition, and debugging.
• You've built data infrastructure under real regulatory constraints at an RIA, broker-dealer, bank, or anywhere SOC 2 or Reg S-P shaped what you built and how.

Benefits

Additional Information

Most wealth management is fragmented. Range is building AI-powered wealth management that actually works. One platform - investments, taxes, retirement, estate - all of it. All helping members manage financial complexity. Backed by Google's Gradient Ventures, Cathay Innovation, and Scale Venture Partners. Hyper-growth. Small team. Every person matters.

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