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How do you build a reliable pipeline when the tools haven't even been chosen yet? As Data Engineer at Budget Thuis, you'll help lay the technical foundation for how a Dutch energy supplier uses its data, from warehouse to orchestration. Curious what that looks like in practice? Read on. What You'll Do As Data Engineer, you'll be one of the first members of our new data team and help build our data platform from scratch. Help evaluate and choose the tools for our data stack: data warehouse, ELT, and orchestration. Build and maintain data pipelines of low to medium complexity once the foundation is in place. Add data quality checks to every pipeline change: null checks, row counts, schema validation, and dbt tests (or equivalent) as standard practice, not an extra step. Break your work into small, deployable increments and keep pull requests focused. Monitor pipeline outputs after every deployment and keep the codebase easy to work with. Respond quickly to pipeline failures, investigate the root cause, and escalate when an issue is bigger than you. Review pull requests with constructive feedback, pair with teammates on complex work, and support colleagues where needed. Communicate early when changes affect downstream consumers such as BI, ML, or customers, and prioritize based on customer impact. Build a concrete growth plan with your manager and share what you learn from mistakes. About the Team You'll work closely with our Senior Engineering Manager, Data Platform, and the BI team, who rely on your pipelines every day. The data platform team is brand new, so you'll help set up not just the pipelines, but also the tools and ways of working around them. We haven't locked in our stack yet, which means your input on choices like the data warehouse or orchestration tool actually counts. It's a small team, so you'll see the direct result of your work and have room to shape how things get done.
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.