Data Engineer to Kreditz

As a Data Engineer at Kreditz, you will have a multifaceted and vital role. You will step into one of Europe’s fastest-growing FinTech scaleups and take full ownership of the company’s Data Warehouse, pipelines, and reporting enablement. We believe this role is perfect for someone who loves building scalable data infrastructure and wants to work close to both product and real business impact. Here, you will become part of a driven organization with endless opportunities for growth!

About the role

You will be part of the Product team and play a crucial role in Kreditz’s continued growth journey. At Kreditz, data is not just a support function – it is the core of the entire product. The company turns raw bank transactions into real-time insights that power credit and risk decisions across Europe.

As a Data Engineer, your mission is to build, evolve, and maintain a scalable, reliable, and high-performing data platform. You will work closely with the business to strengthen the data foundation and enable smart, cost-efficient reporting and analytics for both internal and external stakeholders.

What Kreditz Offers You

• A unique growth journey: The chance to be part of a once-in-a-lifetime journey from startup to global scaleup.
• Real impact: A role where everyone in the team plays a crucial part in the company’s success, and where you get true ownership of the data infrastructure.
• A strong company culture: A fun-loving, driven, and passionate work environment that celebrates progress, humility, and teamwork – we win together.
• Perks & Benefits: 24/7 access to a gym, sauna, and sports facilities at the office, plus a wellness allowance and a competitive base salary.

Work tasks

You will be responsible for the end-to-end data lifecycle, from maintaining the DWH architecture to ensuring data quality for both analytical and operational needs across the company.

• Maintain and enhance the Data Warehouse architecture for scalability and cost-efficiency
• Design and build robust ETL/ELT pipelines within the AWS ecosystem
• Automate internal reporting and create self-service data environments for stakeholders
• Manage AWS services including Glue, Redshift, Athena, and Lambda
• Implement monitoring and validation frameworks to ensure data integrity
• Collaborate with DevOps and Backend teams to align infrastructure
• Support AI and ML models by assisting with specialized data pipelines

We are looking for

• BSc / MSc in a quantitative subject, i.e., Physics, Engineering, Mathematics, Computer Science or equivalent.
• Proven experience working as a Data Engineer or in a similar role focusing on data infrastructure.
• Strong practical engineering skills with a solid foundation in SQL and programming (e.g., Python).
• Strong hands-on experience with AWS (specifically services like Redshift/Snowflake, S3, Glue, and Lambda).
• Solid understanding of data warehousing concepts (e.g., Star Schema, Kimball) and modern data stack tools.
• Experience with orchestration tools (e.g., Airflow, Dagster) and CI/CD workflows (i.e., GitHub Actions).
• Ability to translate complex technical data structures into clear insights for non-technical stakeholders.
• Professional fluency in English, both written and spoken, as this is the company’s working language.

It is meritorious if you have

• Experience with Infrastructure as Code (Terraform).
• Experience from FinTech, Open Banking, or working with highly regulated data.
• Familiarity with BI tools (e.g., AWS QuickSight, PowerBI...etc)

To succeed in the role, your personal skills are:

• Orderly
• Stable
• Responsible
• Intellectually curious

Our recruitment process

This recruitment process is handled by Academic Work and it is our client’s wish that all questions regarding the position is directed to Academic Work.

Our selection process is continuous and the advert may close before the recruitment process is completed if we have moved forward to the next phase. The process includes two tests: one personality test and one cognitive test. The tests are tools to find the right talent for the right position, to enable equality, diversity, and a fair process.