Are you an experienced Data Engineer with deep expertise in enterprise data warehouse design and data modelling, preferably with experience in Data Vault 2.0? Join us in transforming our existing GCP data platform into an advanced enterprise data warehouse that reliably integrates diverse data sources and helps shape the future of finance.
SEB is more than a bank. We are a technology-driven financial institution where everything starts from our customer needs and business outcomes. Cloud, AI, automation and modern engineering are natural parts of how we build, operate and continuously improve our technology platforms. From core banking platforms to hybrid and multi-cloud infrastructure, cybersecurity, platform engineering, AI-enabled operations and automation, we offer a broad tech landscape and many paths to grow. Together, we are shaping secure, responsible and future-proof solutions for our customers and society. Are you ready to take on a new challenge?
About The RoleYou will play a key role in transforming SEB’s Finance & Risk Data Platform into a modern, scalable, and audit-ready enterprise data warehouse. This is a hands-on data engineering role with a particular focus on enterprise data modelling. As part of the FR360 Data Platform team, you will help establish a data architecture that enables reliable integration at enterprise scale while meeting the high standards of a regulated banking environment.
Your primary focus will be designing and implementing robust data models that support business reporting, regulatory requirements, historical data management, and data governance. You will work closely with data engineers, architects, business stakeholders, and Finance & Risk specialists to ensure that data is accurate, traceable, and fit for purposes.
Key responsibilities include:
- Take end-to-end responsibility for data modelling, from source analysis to the design and implementation of target data models.
- Use SQL and other analytical techniques to understand source data structures, content, relationships, keys, grain, and data quality.
- Design target data models using scalable and maintainable patterns based on Data Vault 2.0 principles and methodologies.
- Define and promote standards for historical data management, auditability, lineage, metadata management, and data quality.
- Build and optimise ELT processes using Google Cloud Platform technologies, including BigQuery, Cloud Composer, dbt, and Dataform.
- Drive best practices in data modelling, warehouse design, and engineering excellence across the team.
You will share responsibility for the team’s day-to-day data engineering work while taking a leading role in data modelling, data governance, and data engineering standards.
To thrive in this role, we believe you have:
- * Deep expertise in data modelling and enterprise data warehouse design.
- Proven hands-on experience delivering data models end to end, from requirements gathering and source analysis through conceptual and logical modelling to physical design and production implementation.
- A track record of building scalable data platforms that integrate large numbers of heterogeneous source systems.
