Data Engineer, Internal Platform

Location: San Francisco, CA

About Bland

At Bland.com, our goal is to empower enterprises to make AI-phone agents at scale. Based out of San Francisco, we're a quickly growing team striving to change the way customers interact with businesses. We've raised $100 million from Silicon Valley's finest; including Emergence Capital, Scale Venture Partners, YC, the founders of Twilio, Affirm, ElevenLabs, and many more.

The Internal Platform Team builds the systems Bland runs on: revenue, finance, HR, security, and operations. We've already shipped internal apps for billing, commissions, sales reporting, and marketing attribution. As the company scales, we make sure the business behind the product scales with it.

The Role

As a Data Engineer on the Internal Platform Team, you'll help build the backbone of how Bland runs itself. You're not just writing pipelines, you're designing the single source of truth every team at Bland makes decisions from. Your work decides whether leadership trusts the numbers, or spends the week reconciling spreadsheets.

You'll start by taking control of our data and designing the warehouse from the ground up. From there, the role grows into the APIs, automation, internal tools, and AI agents that run on top of it. The work spans finance, sales, marketing, ops, and security, so it's never one-dimensional.
You'll work directly with our internal platform lead, and your opinions will shape how we build, what we prioritize, and where the platform goes next.

What You’ll Do

• Take control of the data: Design our warehouse from the ground up. You decide how data lands, how it's modeled, and how the company comes to trust it.

• Unify every source: Bring in billing, contracts, usage, CRM, and marketing data with incremental imports, backfills, and full historical tracking.

• Define the shared language: Build the customer mappings and shared models for contracts, billing, usage, sales, and marketing that every team works from.

• Keep it honest: Own pipeline monitoring, data-quality checks, access controls, performance, and cost.

• Then build on top of it: Reporting views for dashboards, context for internal AI agents, and the APIs, automation, and internal tools the company needs next.

The Types of Problems to Own

• One customer, many shapes: A customer has three product orgs, two billing accounts, and several sales opportunities. Connect them without double-counting revenue or losing their history.

• Contract vs. reality: The contract says quarterly billing, but the system generated monthly invoices. Catch it, and show finance exactly what needs correcting.

• Rewinding the pipeline: A deal's amount, owner, and close date have all changed. Reconstruct what the pipeline looked like at the end of last quarter.

• Two apps, two numbers: Find which assumptions differ, and land on a shared definition without throwing out legitimate exceptions.

• AI that gets it right: When an employee asks an internal agent about a customer, it should answer with accurate, current data that the employee is allowed to see.

Who We’re Looking For

• You want to own the whole thing: You'd rather design a system end to end and watch the company run on it than polish one small piece of someone else's.

• You run toward ambiguity: Hand you a messy problem and you'll investigate it on your own and carry it through to something that works.

• Wrong numbers keep you up at night: You test edge cases, reconcile outputs, and retest after every change.

• You build with AI, and you own the result: You can explain your code, defend your decisions, and prove it works.

• You follow through: You take feedback and close the loop on corrections.

• Strong fundamentals: Strong SQL, plus the ability to build services and integrations in Python or another general-purpose language.

• You've shipped: Meaningful technical work through a job, an internship, or a substantial project.

Bonus Points If You Have

• Experience with financial reconciliation, customer identity, or production data pipelines. If so, tell us about a specific problem you solved and how you verified the outcome.

How We Work

We work hard, and we move fast. What you ship here gets used right away, so you'll see the impact in days, not quarters. Finance closes the month faster, sales trusts its pipeline, and leadership makes calls on numbers you built.

We're also deeply collaborative. You'll work side by side with engineering, finance, sales, and ops, and you'll always have teammates to think through a problem with. Everyone pitches in, shares context openly, and wants each other to win.

Benefits and Pay

• Healthcare, dental, vision, all the good stuff

• Meaningful equity in a fast-growing company

• Every tool you need to succeed

• Beautiful office in Levi's Plaza, SF with rooftop views

If you don't have the perfect experience that is fine! We're a bunch of drop-outs and hackers. Working at a start-up is really hard. We work a lot and we figure things out on the fly.