Data Engineer

🚀 Ready to turn data into business superpowers? Hey there 👋! We're Bizzy - and we're on a mission to build an AI Sales OS that gives sales and marketing teams superpowers to spot opportunities, create interest and close deals. We're scaling fast, and to power our next phase of growth, we're looking for a Data Engineer who's not just into clean code, but into clean, powerful, business-changing data. You've had your first real years in data engineering, you've shipped pipelines that people depend on, and now you want to grow faster in a team that will give you real ownership. If that sounds like you - keep reading. You might be exactly who we're looking for. 📍 Based in Ghent, with flexibility to work from home 2 days a week. 🔥 What you'll be doing Build the backbone – Build and maintain the data pipelines that keep our platform fresh, working alongside senior engineers on design. Connect the dots – Integrate diverse data sources like public registers, trade data, and intent signals into one powerful stream of insights. Keep it clean – write the tests, checks and monitoring that keep our data reliable, and help shape how we do quality. Help shape the big picture – Influence key data infrastructure decisions and help leadership make strategic, data-driven choices. Automate the boring stuff – Create tools to monitor, transform, and validate data so we can focus on what matters. Use AI smartly – Explore how AI and ML can enhance our data pipelines, improve data quality, and unlock new insights at scale. Learn and multiply – Learn from experienced engineers through code reviews and pairing, and share what you pick up with the team. #UnitedByGrowth 💡 What makes you a great fit Hands-on data engineer – Around 3 years of experience in data engineering, or a close role such as analytics or backend engineering with a data focus. You've built and run pipelines in production.. Solid foundations of the modern data stack – Strong in Python and SQL , with experience on at least one cloud platform (Google Cloud is a plus). Spark or Databricks experience is a bonus, not a requirement. You'll learn our stack here. Pipeline builder – You've built ETL/ELT pipelines and you care about reliability, performance and code someone else can maintain. AI-curious & future-focused – You actively explore how AI and machine learning can improve data processes. You know when to experiment and when to ship. Quality-obsessed – Testing and monitoring are part of how you build, and you want to learn how to do them at scale. People-first mindset – You ask for feedback, give it honestly and share what you learn. #CandidCandor Business-aware – You understand that great data engineering isn't just about technology — it's about enabling the business to make smarter, faster decisions. Startup-ready – Fast-paced environments excite you. You embrace change, tackle challenges head-on, and know how to prioritize what truly matters. Strong ownership and…