About the job
Are you ready to lay the groundwork for tomorrow's data solutions at the iconic Van Nelle Factory in Rotterdam? In a world where data is abundant, finding reliable information is a rarity. At KVL, we believe that a dashboard gains its value only when backed by a solid data architecture. As a Data Analytics Engineer, you will be both the architect and the builder. Your role involves transforming business questions into clean, scalable data models within a modern data stack.
What We Offer You
Salary: Your indicative salary at this level ranges from €3,800 to €5,890 (based on experience). Your salary will evolve with your development and commitment, with the potential to grow to €8,480 (Master's level);
Collaboration with KVL Colleagues: Work closely in a tight-knit team at the client site, supported by experienced KVL colleagues;
Development: Enjoy substantial responsibilities and opportunities for growth through an entrepreneurial plan and T-Shaped development;
Knowledge Sharing: Stay updated through intensive knowledge-sharing events with fellow KVL Data Engineers;
Secondary Employment Conditions: 26 vacation days, pension scheme, reimbursement for laptop and phone, corporate fitness, and a work-from-home budget;
Mobility: Company car or public transport subscription.
Company Culture: A warm, people-oriented culture focused on personal growth and job satisfaction, complemented by regular fun activities and social gatherings with colleagues;
Social Impact: Work for socially engaged organizations like Mercy Ships Holland and Stichting Jarige Job.
Working as a Data Analytics Engineer at KVL
At KVL, you operate at the intersection of data engineering and analytics. While pure engineers focus on the pipeline, you begin by structuring the truth. Your goal is to ensure that data is not just 'available' but also 'usable'.
You will work with cutting-edge technologies such as Microsoft Fabric, Azure, and Databricks. Your responsibilities include ingesting data, structuring, and modeling it (think Star schemas or Data Vault) for our clients ranging from ambitious medium-sized companies to large players who can rely on their reports. You apply software engineering principles to data: version control, testing, and automation are the norm for you, not the exception.
Kaspar, KVL Data Analytics Engineer at KVL: "At KVL, I am not only the engine behind the pipelines but the architect of a reliable foundation in Databricks; I transform raw data into a platform that genuinely adds value to the entire organization."

