Your role
As a Lead Data Engineer – Finance BI, you will be a senior technical and people leader responsible for shaping, delivering, and sustaining enterprise grade data engineering solutions that support finance reporting and analytics. You will provide technical direction, help ensure the platform is stable and scalable over the long term, and support the data engineering capability so it can deliver reliable, high quality financial data that helps people make better decisions.
You will work closely with Finance BI and other stakeholders to turn business requirements into practical and sustainable technical solutions.
What will you do?
- Lead enterprise scale finance data engineering solutions for reporting and analytics use cases
- Define and govern data pipeline architecture, engineering standards, and best practices to ensure robustness and maintainability
- Translate complex finance requirements into sustainable technical solutions in collaboration with Finance BI and stakeholders
- Ensure data accuracy, reconciliation, auditability, and fitness for purpose
- Establish and enforce data quality frameworks, monitoring, and governance controls
- Lead and develop the data engineering capability, ensuring growth, delivery quality, and knowledge sharing within the team
- Drive continuous improvement across platforms, tooling, and processes to improve performance, reliability, and cost efficiency
- Act as a senior technical and business partner, influencing architectural decisions and constructively challenging requirements
To succeed, you will need
- Minimum 5+ years’ experience in data engineering, BI, or related roles within a complex, multinational organisation
- Proven experience delivering data platforms and pipelines, preferably in finance or financial reporting environments
- Experience operating in a senior or lead capacity, setting technical direction and mentoring engineers
- Expert level SQL, including optimisation of complex and high-volume workloads, with hands-on experience in Databricks (PySpark) in production environments
- Advanced Python skills applied to data engineering and automation
- Strong understanding of data modelling approaches (e.g. star and snowflake schemas) and finance data domains, including reporting cycles, KPIs, reconciliation, and data accuracy requirements
- Strong communication skills with ability to explain complex technical topics to business stakeholders
- Fluent English
In return, we offer
Good level of work-life balance. Working hours reduced to 37.5 hours per week, 5 weeks of vacation and 3 days off, various wellbeing activities such as seminars/workshops on related topics, Multisport card/wellness vouchers.
Hybrid work model (combination of home office and work from our modern offices near the city center), pleasant environment, and a great team of people.
Wide range of opportunities for further professional growth and development within the company, supportive management, clear career path, and development plans.
Vast portfolio and support of your continuous learning – e.g., access to LinkedIn Learning, soft skills trainings, language courses.
Annual salary increase, contribution for pension insurance, contribution for daycare for children up to the age of 3 years.
