SEB isn’t just a bank – we are also a modern technology company with many talented IT professionals, including product owners, business developers, finance and risk experts, analysts, architects, and software developers. More than 200 systems and applications supporting our products, business processes, channels, and data are created and maintained within the Product & Technology Development department.
You will join the Local Regulatory & ESG Reporting team within the Finance, Risk and Data Tribe, developing reporting solutions that support local financial regulatory and ESG (Environmental, Social and Governance) reporting across the Baltics. The role combines reporting development, data analysis, and technical problem-solving, giving you the opportunity to work at the intersection of technology, finance, regulation, and sustainability while improving and modernising critical reporting solutions.
We are open to both Mid and Senior level profiles. Mid-level colleagues are expected to independently own end-to-end tasks, while Senior colleagues take broader ownership and helping the team navigate more complex or ambiguous topics.
It would be an advantage if you have experience with:
Develop and maintain end-to-end regulatory and ESG reporting solutions across the Baltics, translating business requirements into accurate outputs through data analysis, transformation, validation, and technical problem-solving.
Develop and maintain end-to-end regulatory and ESG reporting solutions, translating business requirements into accurate outputs while improving data processes and resolving reporting issues.
Develop end-to-end regulatory and ESG reporting solutions across the Baltics, translating business requirements into reliable outputs through data analysis, SQL or Python development, troubleshooting, and continuous improvement.
Build, optimize, and future-proof modern data platforms using Microsoft Fabric, Azure Synapse, and Databricks, supporting cloud migrations and the full analytics chain from data collection to decision support.
Design and optimize production data pipelines on Databricks, integrating diverse sources and applying data transformations, modeling, quality controls, and Spark performance tuning to deliver scalable data solutions.
