Senior Data Engineer

Description 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