Senior Data Engineer - Ascot Lloyd

We are seeking a Senior Data Engineer to join our Azure-native data team in a leading UK financial services firm. This role is key to maintaining and evolving our data platform, supporting both ongoing enhancements and greenfield development. You will work on data integration, ETL pipelines, analytics, and AI-driven insights, ensuring robust data solutions that support business growth.

This is a hybrid role, with an expectation of three days per week working from the Birmingham office and at least monthly travel to London or other offices.

You will design, build and optimise data pipelines, data models and analytics solutions across SQL Server, Azure Data Lake and Power BI and lead the strategic migration to Microsoft Fabric as the data Platform. You will also support a production Azure Synapse Analytics environment to ensure current business requirements continue to be met.

You will work within an Agile Scrum framework, delivering work through the Azure DevOps backlog, and will help integrate machine learning and AI models into our data processes as we expand our advanced analytics and insight capabilities.

The Senior Data Engineer will coach and mentor Data Engineers and Power BI developers, enhancing their expertise and capability. You will provide design and engineering leadership to build, maintain and shape the future data architecture.

Collaboration is central to the role. You will work within an Agile Scrum environment, using Azure DevOps for backlog management and version control, and contributing to mentorship and knowledge sharing within the team.

This is an opportunity to make a real impact in a small, skilled team, helping shape the firm's data strategy and capabilities.

Technical Skills

Data Integration & ETL

• Data Engineering & Platforms: Strong experience designing and delivering data pipelines, data models and analytics solutions with a Microsoft Fabric-first mindset, helping to accelerate adoption of Fabric (e.g. Lakehouse, Warehouse, OneLake), while also supporting and enhancing existing SQL Server, Azure Data Lake and Azure Synapse Analytics environments in production.
• Integrate multiple external and internal systems data sources into Fabric Data Platform. API integration experience is necessary.
• ETL Development: Skilled in designing and optimising ETL workflows, with knowledge of best practices for data transformation, validation, and loading.

• Power BI: Proficiency in developing, publishing, and managing Power BI reports and dashboards, with strong data visualisation skills.
• SQL & Data Management: Advanced knowledge of SQL for querying, transforming, and managing data, with hands-on experience in SQL Management Studio.
• Azure Machine Learning: Some experience desirable in implementing machine learning models within Azure Machine Learning to enhance reporting and predictive analytics.

• Azure Data Lake: Knowledge of Azure Data Lake for efficient storage and retrieval of large datasets.
• Azure Synapse Analytics (Familiarity): Familiarity with Azure Synapse, with the potential to transition to it for complex data processing needs in the future.

• ChatGPT / Copilot Integrations: Experience integrating with ChatGPT or Microsoft Copilot to automate data processing or enhance analytical insights.

• Source Control: Experience with Git or other version control systems, ideally within Azure DevOps for seamless integration with CI/CD.
• Azure DevOps Backlog & Agile: Skilled in working with an Agile Scrum framework, including managing work items in Azure DevOps and completing deliverables within a 2-week sprint cadence.

• Documentation & Knowledge Sharing: Excellent documentation practices for data pipelines, analytics models, and processes, ensuring knowledge transfer and transparency.
• Mentorship & Leadership: Committed to mentoring data engineers, providing guidance on best practices, technical skills, and professional development.
• Problem Solving & Adaptability: Capable of resolving complex data challenges and adapting solutions to changing business requirements.
• Collaboration & Communication: Strong communication skills for working effectively with cross-functional teams, including data scientists, product teams, and stakeholders.
• Financial Services sector and specifically Wealth Management experience or working in a highly regulated sector will be an added advantage.