Senior Data Engineer, Azure

The Role:

Senior Data Engineer required by global banking organisation to help build and scale a modern data platform within a complex financial services environment. This role plays a key part in bringing together data from multiple regions into a single, well-governed and scalable platform built on Microsoft Fabric and Azure.

You’ll work closely with business stakeholders, product owners and federated data teams to design and deliver a shared data model that supports incremental business outcomes while improving consistency, quality and reuse across the organisation.

This is a hands-on role with real influence over data architecture, engineering standards and ways of working.

Key Responsibilities:

• Designing and evolving a shared enterprise data model in collaboration with stakeholders
• Translating product and business requirements into robust data solutions
• Building secure, observable and performant data pipelines using modern engineering practices
• Integrating, cleansing and curating data using a medallion architecture approach
• Ensuring data quality, integrity and completeness across datasets
• Optimising pipelines, processing workflows and warehouses for performance and cost
• Working closely with analysts and data scientists to enable downstream use cases
• Embedding security, monitoring and operational best practice into all solutions
• Contributing to engineering standards, patterns and best practice across data teams
• Supporting CI/CD improvements in partnership with DevOps
• Keeping up to date with the Microsoft Fabric roadmap and introducing new capabilities where appropriate
• Helping define effective delivery processes for new data products

Key Requirements:

• At least 5 years’ experience working in cloud-based data engineering roles
• Proven track record delivering complex, enterprise-scale data solutions
• Comfortable working across multiple teams, domains or business units
• Strong experience in data modelling and database design
• Excellent Python and SQL skills
• Hands-on experience with Microsoft Fabric and Azure data services
• Experience with technologies such as Azure Data Factory, Synapse, SQL Server and Power BI
• Solid understanding of data warehousing, lakehouse and datalake architectures
• Familiarity with modern data engineering patterns (ETL/ELT, medallion architecture, observability)
• Experience working with Apache Spark and large-scale data processing