Data Engineer

The Data Engineer sits within the Finance Insights team and plays a key role in modernising the Finance function  team is rapidly deploying new technology automation and analytics across Finance with a focus on people processes optimisation and automation. The role holder will work directly with Finance users to understand their day-to-day challenges and design Python-based tools data pipelines and analytical solutions that streamline workflows reduce manual effort and surface richer insight from the Banks financial data.

The role combines hands-on development with applied analytics machine learning and AI helping Finance move from manual reporting to a scalable insight-led operating model. All development deployment and operation takes place within the Banks Microsoft Azure environment and the role holder will be expected to design build and run Python solutions natively on Azure. It directly supports Shaw brooks best of both ethos combining deep human expertise with advanced digital tech and data capabilities.

Key Responsibilities

• Partner with Finance users to rethink how the function works identifying opportunities for process optimisation workflow automation and AI/ML-driven insight that improve efficiency decision-making and business outcomes.
• Design build and maintain Python-based tools scripts and data pipelines that automate recurring finance processes such as month-end reporting reconciliations data preparation and control checks.
• Develop analytical models dashboards and self-service tools that turn finance data into actionable insight for FP&A Financial Control and the wider Finance function.
• Apply machine learning and AI techniques (e.g. forecasting anomaly detection classification document and text automation) to relevant finance use cases using established Python libraries and frameworks.
• Work closely with the CTO Data Engineering team on architecture platform functionality and data availability ensuring Finance gets the best out of the Banks data platform and that the right data pipelines are in place; design and build data pipelines directly where needed to support Finance use cases.
• Apply strong software engineering standards including version control (Git) code review testing documentation and CI/CD to ensure solutions are reliable scalable and maintainable.
• Ensure all solutions meet the Banks data governance security change management and regulatory control requirements working closely with Technology Data and Risk teams.
• Coach and upskill Finance colleagues on Python data tooling and automation good practice helping to embed a self-service insight-led culture across the function.
• Use AI tools (e.g. Claude LLMs MCP servers and agentic frameworks) to work smart day-to-day and integrate AI capabilities into Python solutions and the Banks Web App / Azure environment to deliver intelligent automation and insight at scale.
• Deploy and operate Python solutions on the Banks Microsoft Azure platform end-to-end including CI/CD pipelines configuration and secrets management monitoring and logging (e.g. Application Insights) and adherence to Azure security and identity standards

Qualifications :

Skills & Experience

Essential

• Strong commercial Python development experience including pandas Num Py and modern tooling
• Practical experience applying machine learning and AI techniques in a business setting with familiarity across common Python ML/AI libraries and model types
• Hands-on experience using AI tools to accelerate development (e.g. Copilot LLMs) and integrating AI capabilities into Python applications including via MCP servers APIs or agentic frameworks deployed into the Banks Web App / Azure environment
• Strong hands-on experience designing deploying and operating Python solutions on Microsoft Azure including services such as App Service Functions Azure SQL Data Factory Key Vault Entra  Azure Dev Ops (or Git Hub Actions) for CI/CD.
• Strong SQL skills with a deep understanding of data including modelling structures and quality and hands-on experience working with relational databases and/or cloud data warehouses (e.g. Snowflake SQL Server Postgres Big Query).
• Some financial or finance-function experience with working knowledge of areas such as general ledger management reporting reconciliations budgeting and forecasting or regulatory reporting.
• Comfortable sitting with business users to elicit requirements challenge assumptions and shape solutions collaboratively.
• Experience with version control (Git) code review and CI/CD plus a disciplined approach to testing documentation coding standards and governance.
• Strong written and verbal communication skills able to explain technical concepts to non-technical Finance stakeholders and influence at all levels.
• A proactive problem-solving mindset with strong attention to detail ownership and a continuous-improvement attitude.

Key attributes

• Curious and analytical naturally questioning how things work today and looking for better ways to do them.
• User-focused comfortable sitting with…