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:

• Lead the design and development of a Python-based data processing and reporting platform, driving the migration from SAS
• Own the translation of complex SAS programs into scalable, maintainable, and well-tested Python solutions
• Design robust data processing architectures and pipelines using tools such as pandas, Polars, PySpark, or SQLAlchemy
• Define and implement reusable frameworks, libraries, and best practices for data processing across the platform
• Ensure high code quality through testing strategies, code reviews, and engineering standards
• Collaborate with domain experts and stakeholders to shape solutions, clarify requirements, and challenge assumptions
• Drive performance optimization and scalability for large-scale data processing workloads
• Mentor other engineers and contribute to technical direction and continuous improvement within the team

About you:

• Strong experience with Python in data engineering or data processing contexts (3+ years)
• Deep understanding of data processing frameworks such as pandas, NumPy, and SQL
• Proven experience designing and building scalable data pipelines and architectures
• Strong understanding of relational databases and advanced SQL optimization techniques
• Ability to write clean, maintainable, and production-grade code, and enforce coding standards
• Experience leading technical initiatives and making architectural decisions
• Experience with SAS or strong understanding of similar legacy data processing systems (would be beneficial)
• Experience with scalable data technologies (e.g. PySpark, Polars) and/or reporting tools (e.g. openpyxl, Jinja2), or domain knowledge in financial services (nice to have)

We offer:

Monthly salary range from 4400 EUR to 6600 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!