Data Engineer

About the role

About the role

This role is based in Prague (3 days/week in the office). You build what our clients run on. As a Data Engineer in Keboola Professional Services, you implement data solutions on the Keboola platform for our clients: pipelines, transformations, integrations, data apps and AI use cases that go into production and stay there.

Keboola Professional Services is a small team inside Keboola that builds solutions for new clients and helps existing ones get more out of the platform. You work alongside forward-deployed consultants who own the client relationship and solution design, and who build too. You are the delivery engine: you take a scoped problem, turn it into a working solution, and hand it over in a state the client can own.

You also work in pre-sales. When a deal needs a proof of concept or a deep technical conversation, you build it and present it. Clients meet the people who will later implement their solution, and that is deliberate.

We build agent-first. Coding agents write most of the code. Our engineers own the system around them: the architecture, the environment agents run in (MCP connections, skills, tests and guardrails), several agents working in parallel, and the checks that prove the output is correct before a client ever sees it. Context engineering, meaning capturing a client's data model, metric definitions and business rules in a form agents can use, is as much a part of the job as building pipelines. And more and more of what we deliver is itself for agents: governed data, definitions and skills that let a client's own people hand work to AI.

This role is for someone who gets energy from shipping working things for real clients, and who is comfortable in front of those clients.

What you'll do

Deliver client implementations (most of your time)

- Build data pipelines, transformations, integrations and orchestrations on Keboola for client projects delivered under a statement of work, directing coding agents and verifying what they produce

- Integrate source systems the client actually runs: ERPs, CRMs, accounting tools, databases and APIs, including the messy ones

- Engineer the context: model the data and capture metric definitions, business rules and ownership so that people, reports and AI agents all get the same right answer

- Build agent skills and workflows for clients, so their own teams can delegate real work to agents on top of governed data

- Estimate your own work, deliver against the agreed scope and budget, and raise scope changes early

- Hand over solutions with documentation and enablement that let the client's team run them without us

Build in pre-sales

- Build proofs of concept on the client's own data against agreed success criteria

- Join technical discovery and architecture discussions with client data and IT teams

- Present what you built and explain the design decisions to technical and business audiences