Senior Data Engineer

Location: Boston, MA (Fenway area, hybrid, 2-3 days a week in the office; not open to remote) · Stage: Series A · Reports to: VP of Engineering

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About Vector

Vector is the ABM platform that shows its work. We blend contact-level signals, transparently score every account, put ads in front of the buying committee, and prove they moved pipeline. Every account is staged with evidence, every ad is aimed at a real person, and every dollar maps to pipeline a marketer can see.

Vector was founded by Nick and Josh, who built Drift's sales engineering team together, and is backed by Y Combinator, HubSpot Ventures, and SignalFire. The platform has product-market fit and growing revenue.

Everything a customer sees in Vector starts as data. We ingest 30+ kinds of signals, resolve them to real people, serve them fast, and keep the cost of all of it sensible. That layer is where we need more senior hands.

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The Role

We're hiring a senior engineer who is excellent with data systems and who cares what the customer sees at the end of them. You'll work on four areas that decide whether Vector's product is accurate, fast, and affordable:

• Ingestion: getting the many kinds of signals we collect into shape reliably. That includes website visits, LinkedIn engagement, CRM and marketing-system activity, job changes, company events, buyer-intent feeds, and custom signals customers define, plus large provider data deliveries on S3.
• Identity graph: matching events to real people, and keeping that accuracy up as data and sources drift. Accuracy degrades if nobody looks after it, so you will.
• Serving: getting resolved data to customers and ad platforms quickly enough that the product feels live.
• Cost: keeping warehouse, compute, and storage spend in line as data and customers grow.

A typical week. Engineering at Vector runs in two modes, and you can be dedicated to one of them on any given week. Launchpad is keeping the platform healthy and delightful: triage and support, monitoring, paying down technical debt, and the small touches that make customers smile. Missions are focused, time-bound efforts to solve a specific customer problem, taking it from customer and market feedback to new features and products that drive outcomes for our customers. One week might include digging into a match-rate drop, reviewing a teammate's pull request, and making some cross-cutting infra improvements. Another might be heads-down on a mission.

What you'll do

• Own data problems from the underlying problem to the fix in production, and build ingestion and serving pipelines that survive scale, bad inputs, and partial failure. Examples: a match-rate drop, a customer data accuracy complaint, a cost spike.
• Take cost projects end to end: find the spend, change the system, show the saving.
• Review code, give direct feedback, and help junior engineers and co-ops ramp up.
• Make contributions to the customer-facing application, at first small ones, across our Vue.js and TypeScript frontend and Node.js backend. We want data engineers who can follow a fix through to what the customer sees.

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Who We're Looking For

You have 6+ years of experience, and you've owned data systems in production, including the parts that broke.

You build data systems that work. Pipelines, warehouses, matching or scoring systems, or analytics features, shipped and kept running in production. You can describe the tradeoffs you made.

You care about the customer outcome. You describe your past work in terms of who used it and what changed for them. You've talked to users or measured your work by what they got out of it.

You write real code. You are comfortable in TypeScript or Python, and you can move between a data pipeline and the application that surfaces it. You don't need to be a frontend specialist, but you'll make changes in the application and take it seriously.

You ask good questions when things are ambiguous. We'll hand you problems without a clean spec. Part of the job is working out what's being asked.

You like the early-stage pace. Small team, quick cycles, shifting priorities.

Bonus points: identity resolution, entity matching, or audience targeting experience; ad tech, martech, or B2B marketing platform experience; cost-optimization work on a warehouse or data platform.

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How We Build and Work

Our stack: TypeScript and Node.js on the backend, Vue.js on the frontend, Python, dbt, Prefect, AWS (S3, Aurora, DynamoDB, Redshift Serverless), MotherDuck, Datadog, and omp (Oh My Pi) with CodeRabbit for AI-assisted development and review. You don't need all of it, and we'd rather you learn fast than arrive with a matching list.

We move fast, and we use AI in how we build, not only in what we build:

• omp (Oh My Pi) is our recommended agent harness, and engineers choose the models and subscriptions they like best. If you have a strong opinion, we'd love to hear it!
• CodeRabbit gives AI-assisted code review on our pull requests.
• A shared library of agent skills works across harnesses and covers team workflows, from starting an agent on a Linear ticket to pre-push checks.
• What that looks like: a new signal integration takes us about a day to build.

Our culture is Unculture: Unusual, Unrelenting, Unfiltered, and Unfinished. In engineering it comes down to five tenets:

• Everyone ships. Every engineer, whatever the title, ships code to production for customers. No hands-off architects, no passengers.
• Done is when the customer feels it. A merged PR or closed ticket isn't the finish line. We own the work until a customer or business outcome moves.
• Ship rough to learn. We put unfinished work in front of real customers, controlling who sees it rather than how polished it is. We don't wait for consensus.
• Say the hard thing, and take it. We call out problems early, in reviews and on incidents, even when the better path is harder. And we hear feedback without taking it personally.
• Nothing is finished. We change our minds when shown a better way, and we keep revisiting past work, including how we use AI tooling.

We're a hybrid team that values building together in person. Our Fenway office looks out at Fenway Park.

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What We Offer

• $180,000-$230,000 base salary, with where you land depending on experience and how you do in the interview process
• Meaningful equity at a stage where the upside is real. We'll go through the numbers with you early.
• Full benefits
• Real ownership of systems customers depend on
• A senior seat in a small engineering team, working directly with the VP of Engineering, the Head of Product, and the CEO

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Vector is an equal opportunity employer. We care what you've done and how you think.

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Interview Process

Your job in this process is to vet us as much as we are vetting you.

• Intro conversation with Andrew (VP of Engineering), about 30 minutes: discuss Vector and what you're looking for.
• In-person interview in our Fenway office, about two hours:
  • Technical, about an hour on a real problem we've already solved at Vector. No whiteboard trivia. We care about how you break the problem down, ask questions, and get unstuck. You'll work with Andrew and another Vector engineer.
  • Dig into your experience, about an hour going deep on your previous experience and how it maps to what we need.
• Meet the CEO, Joshua Perk: you're making a bet on us too. This is your chance to ask the hard questions.