Job description

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. ABOUT THE ROLE As a Senior Data Engineer at Range, you’ll be the technical owner of Range’s data infrastructure at a pivotal moment. We’ve grown organically and have different warehouses and a patchwork of ingestions, processes and standards. We’re building the platform, practices and core data model that the next stage of growth depends on. You’ll define the standards, architecture and foundational data model that will shape how we leverage data for years. You’ll also build governance into the foundation that supports our current regulations and the ones we are growing into. This role is ideal for a senior data engineer who's done this before with strong opinions on dimensional modeling and data architecture, comfortable making the foundational calls in a fast-moving environment where the data is regulated. 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 foundational data model. Design how our core entities look and are structured in the warehouse. Make the calls on grain, slowly changing dimensions, snapshot strategy, and the conventions our staging and mart layers are built on. - Set the standards. Define how we do testing, documentation, orchestration, and alerting across all our data infrastructure and bring our existing warehouses up to that bar. - Build and operate the ingestion layer. Design and maintain pipelines that move data reliably from internal and external sources into the warehouse, using Fivetran, dbt and Python where each fits best. Implement the data quality checks, alerting, and troubleshooting tools that let us catch issues before stakeholders do. - Architect for governance. Build role-based access, and audit controls into the foundation so that governance scales with the platform instead of being retrofitted later. - Help shape the platform decision. We're evaluating our long-term data platform and whether to consolidate on what we have or move to something new. You'll partner with our Head of Data and Analytics on the evaluation and own the migration end-to-end once the decision is made. WHAT WE'RE LOOKING FOR - 5+ years of experience in Data Engineering, including time as the most senior data engineer on a team or workstream. - Production experience with a modern data toolset including dbt, a cloud warehouse or lakehouse, and modern orchestration and ingestion tooling. - Strong dimensional modeling fundamentals — you can defend a choice between Kimball, Inmon, or a hybrid based on the problem in front of you, and you've designed type-1/type-2 SCDs in production. - Track record of setting standards on documentation, testing and alerting on a team that didn't have them. WHAT WILL SET YOU APART - You've built data infrastructure under real regulatory constraints at an RIA, broker-dealer, bank or anywhere SOC 2 / Reg S-P / shaped what you built and how. - 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 pipeline development, modeling, and debugging. - You've done a warehouse consolidation or platform migration end-to-end where you made the architectural calls and lived with the consequences and not just executed someone else’s plan COMPENSATION Base salary range: $150,000 – $250,000 This is the base salary range we expect in good faith to pay for this role at the time of posting. Where an offer lands within the range depends on the scope and complexity of work the candidate can own independently and demonstrated depth at this level. OTHER COMPENSATION AND BENEFITS The range above reflects base salary only. Our offer packages also include equity in the form of stock options, so total compensation for this role will exceed the base salary range. We do not ask for or consider salary history. You are welcome to ask questions about compensation at any point in the process. BENEFITS - Health & Wellness: 100% employer-covered medical insurance for employees (75% for dependents), plus dental and vision coverage - 401(k): Retirement savings program to support your future - Paid Time Off: Dedicated time to reset and recharge plus most federal holidays - Parental Leave: Comprehensive leave policy for growing families - Meals: Select meals covered throughout the week - Fitness: Monthly movement stipend - Equity & Career Growth: Early exercise eligibility and a strong focus on professional development - Annual Compensation Reviews: Salary and equity refreshes based on performance - Boomerang Program: After two years at Range, you can take time away to start your own company. We’ll hold your spot for 6 months - and pause your equity vesting, which resumes if you return Range is proud to be an equal opportunity workplace. We are committed to equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. As a company, we are committed to designing products, building a culture, and supporting a team that reflects the diverse population we serve.

Requirements

Must-haves

Set the standards. Define how we do testing, documentation, orchestration, and alerting across all our data infrastructure and bring our existing warehouses up to that bar.
Architect for governance. Build role-based access, and audit controls into the foundation so that governance scales with the platform instead of being retrofitted later.
5+ years of experience in Data Engineering, including time as the most senior data engineer on a team or workstream.
Production experience with a modern data toolset including dbt, a cloud warehouse or lakehouse, and modern orchestration and ingestion tooling.
Strong dimensional modeling fundamentals — you can defend a choice between Kimball, Inmon, or a hybrid based on the problem in front of you, and you've designed type-1/type-2 SCDs in production.
Track record of setting standards on documentation, testing and alerting on a team that didn't have them.
You've built data infrastructure under real regulatory constraints at an RIA, broker-dealer, bank or anywhere SOC 2 / Reg S-P / shaped what you built and how.
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 pipeline development, modeling, and debugging.
You've done a warehouse consolidation or platform migration end-to-end where you made the architectural calls and lived with the consequences and not just executed someone else’s plan
We do not ask for or consider salary history. You are welcome to ask questions about compensation at any point in the process.

Nice-to-haves

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Keywords to mirror

aipython

Platform: ashby
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Benefits

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Dental

Vision

401(K)

Paid Time Off

Parental Leave

Wellness

Professional Development