Recovery Data Expert Data Engineer
Summary
Builds and maintains data pipelines and models for a bank’s credit-risk recovery system using SQL, Python, Snowflake, dbt, and Airflow to deliver accurate, compliant loss data.
Job ID: 3810
About Our Team
Meet the Recovery Data team. Our role is to build and run the Recovery and Loss data solution for high risk customers. The solution primarily supports the bank's credit risk models and ensures regulatory compliance while adding value by providing data‑driven insights into improving debt management strategies, operational efficiency, and customer outcomes. We pride ourselves on delivering high quality automated Recovery and Loss data with accuracy, completeness, and strong governance.
Main responsibilities in this role
- Work closely with stakeholders in Business to turn their business problems into fit‑for‑purpose data solutions
- Gain deep understanding of the Recovery data domain to take ownership of designing and building the Recovery data model
- Take ownership of delivery from requirements to production with long‑term sustainability in mind
- Design and build data pipelines
- Design and develop technical enablers focused on automating everything
- Act as guide to the technical team, ensuring development standards and solid engineering practices are followed
- Set a high standard for delivery, prioritizing long‑term reliability, stability, and maintainability over quick fixes
- Stay current with AI‑assisted development and adopt AI to increase efficiency, maintainability, and reliability
Who You Are
This is the right role for you if you:
- Don’t wait for detailed specifications – you proactively understand the business domain and ask the right questions to clarify the requirements
- Take ownership of the full lifecycle – from design to implementation and testing – and stand by the solutions you deliver
- Understand what good looks like in data warehousing and build accordingly
- Seek to develop deep domain knowledge
- Care about long‑term maintainability over short‑term fixes
- Use AI as a tool to improve productivity, quality, and speed
Your background and skills include
- Degree in Computer Science, Computer Engineering, Information Technology, Data Engineering or a relevant technical field
- Strong experience in data engineering and data warehousing, building large‑scale data solutions
- Comfortable taking full ownership from requirements to production
- Strong SQL and Python skills
- Experience with modern data platforms (Snowflake, dbt, Airflow)
- Excellent data modelling skills
- Experience with enterprise API integration
- Solid engineering practices (Git, CI/CD, automated testing)
It would be ideal if you also
- Have experience with AI and how AI can support development and operations of large‑scale data solutions
Location
The role is based in Helsinki, Finland.