Analytics Engineer

Hi, I'm Daan, Data Lead at FeedbackFruits. 👋

For the past year I've set up the Data function here. In that time I've built our company-wide datalake, dashboards & conversational analytics. We embedded analytics into our EdTech product and built a data API for our users. AI did a lot of the heavy lifting, which is how one person got this far. It's now used across the whole company, and I’ve reached a point where the volume and complexity of it outgrows one person.

So I'm hiring an Analytics Engineer for our HQ in Amsterdam to own and extend this with me. I’m looking for someone early in their career, but not at the start of it. You have shipped data work that other people depended on, and you are ready for a lot more ownership than you have had so far. What I need is enough foundation that you stay in control of what gets shipped, yours as well as the AI's, and that you can explain why you built it that way. If you want to grow quickly into an all-round data professional, while gaining deep experience with a broad range of modern data technologies, this is a good place to do that. My ambition is that within a year you're better than me on the core stack and telling me when I've got something wrong.

We're an Amsterdam-based EdTech company, building tools for better and more active teaching in higher education. It started in 2012 with a group of students and teachers at TU Delft who got stuck on a fairly annoying question: why, in a room full of curious people, does education still run in one direction? Today more than 200 universities in 28 countries use what we built to do something about it, with tools for peer review, oral assessment, interactive video and competency-based assessment, all running on top of whichever LMS they already have. We're a team of around 90, growing steadily, with the same close relationship to educators we started with.

What you'll do:

• Own our data products end to end together with me: the datalake, the dashboards, the MCP for conversational analytics, the data API, and the analytics embedded in our product

• Take a data need from the business and carry it the whole way, from getting new data into the datalake to the moment someone is using it to make a call

• Build the transformation layer in SQL and dbt, and write the Python that moves data around and exposes it, from extraction jobs to API services

• Keep the stack healthy and make it incrementally better: faster models, stronger data quality checks, less technical debt. You spot most of this yourself rather than waiting for it to be assigned

• Turn data into a conclusion with an implication. Not a chart, but an answer a product or GTM team can act on: who isn't adopting, what drives adoption, what we should do differently

• Present that work to product and go-to-market teams, and where it scales better, build them the tooling to answer their own questions

• Work on larger initiatives that fundamentally change how our data stack works, alongside the day to day requests

• Review my work the way I'll review yours

What you bring:

• You've written Python and complex SQL that ran in production and that other people relied on, as well as maintaining it, debugging it, and fixing what you got wrong the first time

• You're comfortable with Git and standard version control workflows

• You use AI tools like Claude Code or Codex in your development work, and you know the difference between output you understand and output you're hoping is right

• You're resourceful. When you hit something you don't know, you dig into the documentation and unblock yourself

• You go after root causes. A small data anomaly bothers you until you understand why it's there

• You can take a business question, turn it into something technical, and say something when the scope needs adjusting

• You handle a broad and sometimes scattered set of requests without losing the thread on the longer-term work

• Experience with dbt, DuckDB, FastAPI, Mixpanel, Azure or Terraform helps, though foundational engineering skill matters more to me than knowing our specific tools

• Available 32-40 hours per week, with 2 days a week from our Amsterdam office

What you get:

• 25 paid holidays per year

• Hybrid work schedule (2 days onsite)

• A day off for your birthday

• Advantageous pension scheme

• 3 days of volunteering leave per year

• €550 Learning & Development budget per year + 3 days paid leave for learning

• Travel allowance and Swapfiets subscription

• Free access to our office gym

• Unlimited access to mental health support via OpenUp (EU, US, and AUS)