Published by Bakari Sumaila - VP Engineering 🔗 Linkedin 🔗 Fullenrich Website
Full-time — US Eastern timezone — Remote
FullEnrich is a B2B data enrichment platform. Sales and go-to-market teams at B2B companies use our product to find contact data (emails, phone numbers) for decision-makers at their target accounts. Think precision prospecting, not mass outreach: our customers sell software, hardware, or services to other businesses, and outbound sales is a fundamental engine of how they grow.
Under the hood, we aggregate 20+ data providers into a waterfall system to maximize coverage. 3,500+ customers including AWS, Shopify, Deel, and HubSpot. Profitable, ~40 people, based between the US & Europe.
We're standing up a dedicated Growth Squad: a small team whose entire job is to move our key metrics by experimenting in production, fast. Activation, conversion, retention, expansion — we have ideas for all of them, and the only way to know which ones work is to ship and measure.
This isn't a roadmap-and-specs team. It's high tempo. We run several experiments a week, sometimes more, straight into production. Some of them work and we keep them; most don't and we kill them. The point is to learn quickly which levers actually move the business, then go back and harden the ones that earned their place.
You'll be the backend half of this squad, working closely with a frontend engineer, and coordinating with people in Europe and on the US West Coast.
Ship experiments fast. Build and launch backend changes that test a hypothesis — a new pricing nudge, a credit-pack variation, an onboarding tweak, a flow that touches how enrichment results are delivered. Get it live, instrument it, read the numbers.
Work inside the existing system. These experiments don't live on a greenfield. You'll be making targeted changes across an existing Go codebase — including, sometimes, the billing and credit system. Not rewriting it, but reaching into it confidently and safely to test something, then backing it out cleanly if it doesn't pan out.
Promote what works. When an experiment proves its worth, you come back and do it properly — clean up the V1, add the tests, make it production-grade. Knowing what to harden and what to throw away is most of the skill.
Measure everything. An experiment without instrumentation is a guess. You'll wire in the tracking that tells us whether a change actually moved the metric it was supposed to.
You're a senior engineer who ships. You've spent enough time in production to be calm about it. You can drop into a codebase you didn't write, understand it quickly, and make a surgical change without breaking things around it.
You're comfortable with a scrappy V1. The growth game is about speed of learning, not architectural purity. You're fine writing code that's good enough to test an idea, on the explicit understanding that you'll either delete it or clean it up later. If your instinct is to spend three months designing the perfect abstraction before shipping anything, this isn't the seat for you.
You can be trusted near billing. Some experiments touch the credit system or billing logic. We need someone senior enough to own that responsibility — to know what's safe to touch, what isn't, and how to test a change to money-adjacent code before it ships.
You're fluent in Go. Our entire backend is in Golang — hexagonal, modular, clean. You should feel at home in a codebase like that.