Senior Data Engineer

Senior Data Engineer | Snowflake & SQL
£85,000–£105,000 | London

Profectus Recruitment is partnering with an established financial services business to recruit a Senior Data Engineer as it continues to invest in its data capability and wider AI and Automation initiatives.

We’re particularly interested in engineers with experience in investment management, wealth management, asset management or broader financial services, who understand the importance of accurate, reliable and well-governed data.

With a migration from on-premise infrastructure to the cloud underway, you’ll play a key role in developing the data pipelines and infrastructure supporting business reporting, analytics and operational needs.

This is a hands-on senior position with scope to influence architecture, work directly with stakeholders and support the development of colleagues within the Business Intelligence team.

The role

• Design, build and maintain automated data pipelines, ensuring data remains accurate, reliable and fit for purpose.
• Help deliver the migration from on-premise infrastructure to the cloud.
• Develop scalable data models and efficient schemas, applying Snowflake optimisation best practice.
• Work closely with business stakeholders to understand requirements and translate them into practical data solutions.
• Monitor production pipelines, investigate issues and improve performance.
• Use Azure DevOps, Git and CI/CD to support testing, deployment and monitoring.
• Contribute to the architectural design of data and business services.
• Mentor colleagues and share engineering best practice.
• Support the discovery, design and implementation of AI and Automation opportunities across assigned business areas.

What we’re looking for

• Substantial hands-on data engineering experience at a senior level.
• Advanced SQL skills, including complex query development and performance tuning.
• Strong commercial Snowflake experience, including optimisation.
• Experience with Azure DevOps, Git and CI/CD.
• A strong understanding of data warehousing, dimensional modelling and scalable schema design.
• Experience building and supporting automated production data pipelines.
• The confidence to work independently, engage stakeholders and take ownership of delivery.

Sector experience

A background in investment, wealth or asset management would be particularly valuable, especially where you’ve supported investment platforms, financial products or reporting. Broader financial services experience is also highly relevant.

You should be comfortable working in a regulated environment where data quality, governance and controls are central to delivery.

Experience with dbt, Python, automated testing, analytics or data science would be beneficial.

Why consider this role?

You’ll combine hands-on engineering with architectural input and direct business engagement. The cloud migration offers an opportunity to shape the data environment, while the wider AI and Automation programme provides scope to contribute beyond core BI delivery.