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