Location: Vilnius, Lithuania

Asset Finance helps customers and businesses finance physical assets such as cars, equipment, and fleets through leasing and loan products across the Nordics. The area covers the full lifecycle of an agreement from sales and onboarding, through contract management and servicing, to reporting and regulatory compliance.

The Asset Finance Tribe builds and runs the digital platforms that make this business possible. We develop and modernise core systems, integrate with dealers and vendors, and enable end to end digital journeys for customers and partners across all markets. The tribe is also driving major transformation initiatives, such as Asset Connect, to create a scalable, modern platform used across the Nordics.

The workplace is located in Vilnius. Danske Bank supports workplace flexibility (we currently use a hybrid work model, where we work at least 3 days in the office).

Please apply as soon as possible, as we conduct interviews on an ongoing basis.

This role does not include a relocation allowance.

You will:

• Contribute to building a modern Python-based data processing and reporting platform, supporting the migration from SAS
• Work with more experienced engineers to convert SAS programs into clean, maintainable, and well-tested Python code
• Support the translation of SAS logic (e.g. DATA steps, PROC SQL, PROC SORT) into Python, pandas, and SQL solutions
• Help develop reusable components and shared utilities to standardize data processing patterns
• Assist in designing and implementing data pipelines using tools such as pandas, polars, PySpark, or SQLAlchemy
• Write unit and integration tests to ensure reliability and quality of the migrated solutions
• Collaborate closely with SAS domain experts and teammates to understand business logic and edge cases
• Support implementation of reporting outputs to replace SAS ODS (e.g. using Jinja2, openpyxl, or similar tools)
• Participate in code reviews, learning and applying best practices and coding standards
• Contribute to improving performance and scalability of data processing, especially for large datasets

About you:

• Hands-on experience with Python in a data processing or engineering context (1+ years)
• Comfortable working with data using pandas, NumPy, and SQL
• Experience building or contributing to data transformation or ETL pipelines
• Understanding of relational databases and ability to write efficient SQL queries
• Ability to write clean, readable, and maintainable code
• Exposure to or interest in SAS or similar data processing tools (nice to have)
• Familiarity with scalable data tools such as PySpark or Polars (would be beneficial)
• Experience with reporting tools (e.g. openpyxl, Jinja2) or domain knowledge in financial services (nice to have)

We offer:

Monthly salary range from 3920 EUR to 5880 EUR gross (based on your competencies relevant for the job).

• Additionally, each Danske Bank employee receives employee benefits package which includes:
• Growth opportunities: professional & supportive team, e-learnings, numerous development programs; (incl. professional certificates); 100+ professions for internal mobility opportunities.
• Health & Well-being: a diverse, inclusive, work & life balance work environment; additional health insurance; mental well-being practices; partial psychologist counselling compensation; silence and sleep zones at the office; game rooms.
• Hybrid working conditions: Work from home up to two days a week; home office budget (after the probation period); modern Danske Campus workplace developed with anthropologist for the best employee experience.
• Additional days of leave: for rest, health, volunteering, exams in higher education institutions, and other important activities. Moreover, for seniority with Danske Bank.
• Monetary compensation package: accidents & critical diseases insurance; financial support in case of unfortunate events, travel insurance; IIIrd Pillar Pension Fund contribution.

See all the benefits HERE.

Your job function (position) in the job contract will be Data Engineering.

If you're interested in this role and joining my team, feel free to contact me Ignas Ivoka - Danske Bank via LinkedIn, and I will answer your questions!