Geïnteresseerd in de volgende banen?
Stuur mij soortgelijke banen
Blijf als eerste op de hoogste en mis geen vacatures.Functieomschrijving
Senior Data Engineer
- Hybrid
-
- Amsterdam , Noord-Holland , Netherlands
- Tech
Job description
At Speakap, we build a mobile-first Employee Experience Platform designed to connect organizations with their frontline and deskless workforce across industries such as retail, hospitality, healthcare, logistics, and production. Our platform supports over 600 customers and more than 1,000,000 users, helping companies improve communication, engagement, and operational efficiency at scale.
With a strong presence in the Netherlands and a growing footprint in the United States, we are entering our next phase of growth and continue to invest in strengthening our product and data capabilities.
We're looking for a Senior Data Engineer who gets energized by building data foundations from scratch and turning raw data into reliable, usable insights.
What you'll actually do
-
Design and build scalable data pipelines from scratch, ensuring reliable data flows across the platform
-
Develop and maintain ELT processes to support analytics, reporting, and product initiatives
-
Use SQL and Python to transform, structure, and optimize datasets for various business and product needs
-
Actively monitor, maintain, and troubleshoot data pipelines.
-
Partner with Product, Engineering, and the CSM to enable data-driven features and decision-making
-
Improve data quality, consistency, and accessibility across systems and tools
-
Implement CI/CD for data services and infrastructure using modern DevOps tools to ensure reliable, versioned, and automated data workflows.
-
Build the data reporting and dashboards that translate raw data into business insights and decision-making.
-
Contribute to a fast-moving environment where pragmatism, ownership, and adaptability are key
What you bring
-
At least a BSc in Computer Science, Data Engineering, Data Science, or a related technical field, with approximately 5 years of relevant experience
-
Strong hands-on experience building data pipelines and workflows from scratch
-
Strong hands-on experience with Snowflake and Airflow (or similar orchestration tools).
-
Solid SQL skills and practical Python experience for data processing and transformation
-
Experience working with modern data stacks or cloud environments (AWS) is a plus
-
Comfortable working cross-functionally with Product and Engineering teams
-
Pragmatic, ownership-driven, and able to work independently, with interest or experience in supporting AI or data-driven initiatives considered a strong plus
Bonus: Interest or experience in supporting AI/ML initiatives is a strong plus.
What's in it for you
-
Competitive compensation and meaningful ownership over your work
-
Startup speed with a proven product and real-world scale
-
The opportunity to shape how data supports product and business decisions
-
Exposure to a growing AI and data-driven product landscape
-
A collaborative environment with fast feedback loops and minimal bureaucracy