Manufacturing Jobs in Amsterdam, Netherlands (Now Hiring) — 106 open — Page 6

Be yourself at Protolabs 

Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. We are an equal opportunity employer, and we are committed to building a diverse team that feels they are valued in the workplace. So do you feel you do not meet every single requirement but still intrigued? We encourage you to still apply! You can help make our company even better. We do not discriminate based on race, color, national origin, sexual orientation, gender, age, mental or physical ability, or any way you represent yourself. We strongly believe diversity makes for more successful teams. 

Why Protolabs? 

We are the leaders in digital manufacturing.  We hire doers, makers, and creative thinkers who tackle our roles with an entrepreneurial spirit.  Our culture is centered around meaningful work that brings new and innovative products to market at unprecedented speeds.  We are a diverse team that comes from all walks of life and take pride in our team who is smart, genuine, humble, and passionate about what we do.  It’s our people who fuel our creativity and make our culture feel like home. 

We are looking for a Senior Analytics Engineer  to join our team!

 

This is a hybrid role, and we are accepting applications from candidates based in the Netherlands.

 

The Senior Analytics Engineer plays a critical role in shaping and scaling the data foundations that support analytics and decision‑making across the organization. This role transforms complex, raw data into reliable, well‑structured data products that analysts and business partners can confidently use to drive insights.

Sitting at the intersection of data engineering and business analytics, the Senior Analytics Engineer brings deep technical expertise—particularly in dbt and large‑scale transformation design—to guide the evolution of the analytics platform. Working closely with the Principal Analytics Engineer, this role accelerates the migration from legacy DOMO pipelines to a modern data stack, establishes robust modeling and testing standards, and helps elevate technical best practices across the Analytics Engineering team.

\nWhat you’ll do

• Design, build, and maintain complex, scalable dbt models and projects in large, multi domain environments
•  Act as the team’s dbt expert, including refactoring complex transformations, resolving performance issues, and exploring, evaluating, and introducing advanced dbt features where they add clear value
• Accelerate the migration from legacy DOMO pipelines to the modern data platform in close collaboration with the Principal Analytics Engineer
• Help shape and refine shared approaches to data modeling, documentation, dbt project structure, and overall transformation practices as the platform scales
• Support the team in using AI powered IDEs, coding assistants, agents, and automation tools to improve development workflows and productivity
• Guide and support the growth of other Analytics Engineers, helping them strengthen dbt, SQL, modeling, and problem solving skills
• Collaborate with business stakeholders to understand workflows and metrics, translating real world logic into clear, reliable data models
• Provide Analytics Engineering coverage during EU business hours, partnering closely with EU based stakeholders.

What you’ll bring

Education and Experience:

•  Bachelor’s Degree in Computer Science, Software Engineering, Mathematics, Data Engineering, or a related field
• Minimum of 5 years of experience in analytics engineering, data modeling, or data transformation
• Extensive hands on experience with dbt (or similar transformation tools such as SQLMesh), ideally in large, complex, multi project environments
• Advanced SQL skills, with the ability to refactor complex queries, simplify legacy logic, and optimize transformation
• Strong experience building clear, scalable data models and data products that reflect real world business processes
• Strong business acumen, with the ability to understand how the business operates through data, validate assumptions, and partner effectively with stakeholders
•  Strong problem solving skills and comfort working in ambiguous, complex data environments
• Experience working with data quality practices, including tests, validations, and investigating data issues
• Strong communication skills and the ability to work effectively across technical and non technical teams
•  Comfort with Git based workflows and CI/CD practices

Bonus Points For

•  Experience with modern data platforms
• Familiarity with BI tools (Power BI, Looker, Tableau) for validating downstream data
• Experience migrating legacy analytics environments to modern stacks
• Exposure to data governance or metadata tools.

What's in it for you?\n