Senior Data Engineer – Cyber security / AI

Amsterdam | €90,000–€100,000 + stock options | Permanent

There’s plenty of ambition around what this data platform could become. First, they need someone to take proper ownership of what’s already there.

I’m working with a cybersecurity business building a technically demanding product, with a small engineering team and customers already depending on it. Data moves between systems, services and teams, and the people working on security and AI need to trust what they’re getting.

The existing data ownership is being handed over. That’s why this hire matters.

They need someone who can understand the setup, ask the right questions and get comfortable running it independently. Someone who can investigate a broken integration, improve a model, sort out the underlying problem and leave things easier to maintain for whoever comes next.

You’ll be the primary data engineer, working alongside the wider infrastructure and software engineering team. There are people to work with and learn from, but you’ll need to be comfortable making decisions without another senior data engineer checking everything first.

Quite a bit of responsibility. Quite a bit of influence too.

The immediate work centres on Airbyte, dbt and BigQuery. Maintaining connectors, setting up ingestion, running transformations and making sure the resulting data is accessible and useful.

And, inevitably, working out why something that behaved perfectly yesterday has decided otherwise today.

That’s where the software engineering background matters. You’ll need strong Python and SQL, understand APIs and how systems communicate, and be comfortable getting into the code when configuring a tool doesn’t solve the problem.

Authentication, pagination, incremental loads, changes in source data, retries. The things that determine whether an integration stays reliable after the first successful run.

Airbyte is part of their stack. If you’ve done comparable work with Meltano, Stitch, Fivetran, Glue, AppFlow or custom integrations, I’d like to hear about it.

Tell me what you built, how much you owned and what happened when it broke. That gives me considerably more to work with than a list of tools.

You’ll also need solid dbt experience and familiarity with GCP, particularly BigQuery, Cloud Storage and IAM. AWS and infrastructure experience would be useful around that.

The first few months have a clear purpose: learn the platform, take over its day-to-day operation and start making improvements. There’s an opportunity to explore better orchestration or take ownership of a planned migration once you’ve got your bearings.

Then the remit gets broader.

Lakehouse architecture. A semantic layer that gives teams consistent definitions of their data. Better foundations for AI and MLOps workloads. Decisions about how the platform develops as more people and services depend on it.

You’ll help shape those decisions, and you’ll still be close enough to the implementation to know whether they’re working.

That’s the bit I find interesting here. You get to see the problems first-hand, form a view and do something about them.

Experience with Kafka, streaming, Kubernetes, Helm or Terraform would all be useful. So would experience helping analysts become more self-sufficient. Over time, there’s scope to develop towards Team Lead as the data function grows.

But you need to enjoy the job that comes first. There will be maintenance, smaller improvements and awkward bugs alongside the bigger architectural work. All of it needs an owner.

A few practical bits:

• €90,000–€100,000 base + stock options
• Hybrid working in Amsterdam
• Unlimited paid holiday
• Work-from-home budget and mobile stipend
• An international business with 25+ nationalities
• A funded, growing company with an established product

The process includes an introductory call, a technical conversation, a take-home task with a review and system-design discussion, then a final leadership conversation. I’ll talk you through what to expect.

If you’ve owned a data platform, enjoy the engineering underneath it and want more say in what happens next, give me a shout.

I’d like to hear what you’ve built.