Data Engineer at Deftpower
Arnhem, , Netherlands -
Full Time


Start Date

Immediate

Expiry Date

24 Oct, 25

Salary

4.5

Posted On

25 Jul, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Decision Making, Ownership, Python, Power Bi, Fraud Detection, Plain Language, Mobility, Data Quality, Design, Data Infrastructure, Azure, Data Models, Sql, Dashboards

Industry

Information Technology/IT

Description

At Deftpower we’re looking for a Data Engineer to join our team.
Full-time · Arnhem

You’ll form a strong team with Chris, who holds deep knowledge about how everything is built. Together, you’ll combine your skills and insights to deliver real impact and keep our data infrastructure running smoothly.

  • Build and manage ETL/ELT pipelines;
  • Work with Azure SQL and other Microsoft Azure tools;
  • Combine data from many different internal and external sources;
  • Design scalable, reliable data models;
  • Support fraud detection and other critical use cases;
  • Create dashboards and actionable insights in Power BI;
  • Monitor data quality and enable high-impact decision making
Responsibilities

At Deftpower, we move fast, if you spot something today, there’s a good chance you’ll steer the business with it tomorrow. As our Data Engineer, you build the pipelines and models that turn data into sharp insights. We’re talking terabytes of data, billions of rows, and sources scattered across platforms. You bring it all together, clean it up, and make it usable. From fraud detection to high-stakes decisions that shape our growth, your work matters from day one. You’ll collaborate with product, operations, engineering and finance to make sure our data isn’t just there, but works for us.

You’ll form a strong team with Chris, who holds deep knowledge about how everything is built. Together, you’ll combine your skills and insights to deliver real impact and keep our data infrastructure running smoothly.

  • Build and manage ETL/ELT pipelines;
  • Work with Azure SQL and other Microsoft Azure tools;
  • Combine data from many different internal and external sources;
  • Design scalable, reliable data models;
  • Support fraud detection and other critical use cases;
  • Create dashboards and actionable insights in Power BI;
  • Monitor data quality and enable high-impact decision making.
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