Senior Data Engineer

The Opportunity We are supporting a major data platform transformation within a banking environment, moving from a legacy SQL Server and SSIS-based setup to a modern, scalable architecture built on dbt, Dagster, and OpenShift . This role is not about maintaining existing systems.

It is about rebuilding a critical data platform from the ground up, with direct impact on risk, trading PnL, and core financial data flows . We are looking for a hands-on Senior Data Engineer who can take ownership of complex migration workstreams and deliver reliably in a regulated, high-stakes environment.

What You Will Do You will play a central role in the end-to-end migration and modernisation of the data platform.

Platform Transformation Translate legacy ETL logic from SSIS and stored procedures into modern ELT pipelines using dbt Implement Data Vault 2.0 structures including Raw Vault and Business Vault Build datamarts and curated datasets for downstream analytics and reporting Orchestration & Infrastructure Design and operate workflows using Dagster, including scheduling, dependencies, and recovery mechanisms Deploy and run data workloads on OpenShift / Kubernetes environments Event-Driven Data Processing Enable near real-time data processing using Kafka-triggered pipelines Integrate with upstream data lake environments and external data providers Data Quality & Validation Establish robust data validation and reconciliation processes Implement automated testing and monitoring using dbt Operational Ownership Support production pipelines and resolve incidents when required Create clear documentation and ensure operational readiness Continuously improve performance, reliability, and maintainability What You Will Do You will play a central role in the end-to-end migration and modernisation of the data platform.

Platform Transformation Translate legacy ETL logic from SSIS and stored procedures into modern ELT pipelines using dbt Implement Data Vault 2.0 structures including Raw Vault and Business Vault Build datamarts and curated datasets for downstream analytics and reporting Orchestration & Infrastructure Design and operate workflows using Dagster, including scheduling, dependencies, and recovery mechanisms Deploy and run data workloads on OpenShift / Kubernetes environments Event-Driven Data Processing Enable near real-time data processing using Kafka-triggered pipelines Integrate with upstream data lake environments and external data providers Data Quality & Validation Establish robust data validation and reconciliation processes Implement automated testing and monitoring using dbt Operational Ownership Support production pipelines and resolve incidents when required Create clear documentation and ensure operational readiness Continuously improve performance, reliability, and maintainability Requirements What You Bring Technical Expertise Strong experience with SQL Server and T-SQL, including performance optimisation Proven hands-on experience with dbt in production environments Solid experience with workflow orchestration tools, ideally Dagster Practical knowledge of Data Vault 2.0 modelling concepts Experience working with container platforms such as OpenShift or Kubernetes Familiarity with event-driven architectures and Kafka Domain Experience Experience working with financial data, ideally in banking or trading environments Understanding of risk and PnL data structures is a strong advantage Working Style Strong ownership mindset with the ability to work independently Structured, pragmatic, and delivery-focused Comfortable operating in complex and regulated environments Clear communicator across both technical and business stakeholders What Success Looks Like Within the first months, you will have: Delivered initial Data Vault structures and migrated datasets into the new platform Established stable, event-driven pipelines Ensured data consistency and validation between legacy and new systems Contributed to a production-ready, scalable data platform