Data Engineer

Stockholm, Sweden

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Froda is on a mission to revolutionize SME financing by leveraging data, AI, and machine learning to create intelligent, scalable, and efficient financing solutions. As we expand across Europe, we're focused on building cutting-edge credit risk models, fraud detection systems, and automation processes that empower small businesses to thrive.

We are looking for a Data Engineer to join our growing team and play a key role in shaping the infrastructure and workflows that power data, machine learning, and analytics at Froda.

About the Role

To power our growing ambitions, we are expanding our data & ML capabilities. As a Data Engineer at Froda, you’ll play a key role in designing, building and maintaining the infrastructure and workflows that enable machine learning, analytics, and data products across the company.

You’ll work closely with data scientists, analysts, and other data and analytics stakeholders to create scalable, production-ready pipelines and platforms that drive real business impact — from credit risk and fraud detection to business automation and decision-making.

Together with the rest of the team, you’ll continuously deliver value while improving technical structure and ensuring the reliability and scalability of our systems.

Who are you?

We believe that you are a systems-oriented engineer who is passionate about enabling machine learning and analytics at scale. You’re curious, analytical, and love turning complex problems into robust technical solutions. You enjoy collaborating across teams, sharing knowledge, and contributing to a data-first culture.

Your Experience:

  • 3 to 5+ years in a similar role, ideally within tech- and product-driven companies

  • Designing and building robust data pipelines in production environments

  • Working with cloud-based data warehouses (e.g., Snowflake) and streaming platforms (e.g., Kafka)

  • Building and maintaining ML-Ops platforms or similar infrastructures

  • Working with Python, SQL, and orchestration tools like Airflow or DBT

  • Using Docker and Kubernetes, and deploying models via APIs (e.g., FastAPI, KServe)

  • Cloud platforms such as Azure or similar

  • Feature stores and reusable ML pipelines (strong plus)

As Swedish is our primary working language, we’re looking for someone who’s fluent in both Swedish and English.

What’s in it for you?

At Froda, you’ll be part of a company that combines the best of both worlds – a fast-moving, high-energy culture with the stability and structure to support long-term success. We’re 100+ ambitious self-starters who genuinely care for each other and the work we do, all while having fun together.

Here, you’ll have the opportunity to take ownership of your work, develop your skills, and shape your own growth journey. With big ambitions and a rapidly evolving business, there’s plenty of room to grow, lead initiatives, and make a real impact on both our company and the industry. If you're looking to be part of a success story and contribute to something bigger, this is the place for you.

Furthermore, you’ll get:

  • An opportunity to be part of an exciting journey, shaping the future of our company and transforming the SME financing landscape

  • Fabulous office overlooking Stockholm and a friendly culture that values work/life balance

  • We prioritize working in the office to maximize the positive impact of in-person collaboration, but we offer flexibility with work hours and remote work

  • Competitive compensation package

  • Insurance and pension plan

If you're excited by our mission of building the tech that powers funding for thousands of entrepreneurs, apply or tell a friend!


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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  3  2  0
Category: Engineering Jobs

Tags: Airflow APIs Azure Credit risk Data pipelines dbt Docker FastAPI Kafka KServe Kubernetes Machine Learning MLOps Pipelines Python Snowflake SQL Streaming

Perks/benefits: Career development Competitive pay Startup environment

Region: Europe
Country: Sweden

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