Senior Data Engineer

Role overview: Data is the fuel for every AI solution we build — and we're looking for someone who can own that foundation end-to-end. As a Senior Data Engineer, you'll design and deliver scalable cloud data solutions on Microsoft Azure and Fabric, combining hands-on engineering with real technical leadership: owning solution design, setting the standards your team works to, and mentoring the engineers around you. Key responsibilities: - Design and develop batch and streaming data pipelines using Azure Data Factory, Fabric Data Factory, notebooks and related services. - Build curated lakehouse, warehouse and semantic data layers that support analytics and AI use cases. - Implement data-quality checks, metadata, lineage, monitoring, alerting and operational support. - Optimise pipelines and storage for reliability, security, performance and cost. - Apply source control, automated testing and CI/CD through Azure DevOps or GitHub. - Own delivery of your workstreams end-to-end — from design through to production, managing risk and stakeholders along the way - Set the bar for engineering quality — reviewing designs, shaping standards, and mentoring the team to raise the floor, not just the ceiling. Qualifications, skills and experience: - Significant data-engineering experience with SQL and Python or PySpark. - Hands-on experience with Microsoft Fabric or Azure services such as Data Factory, Data Lake Storage, Synapse Analytics and Databricks. - Knowledge of dimensional modelling, lakehouse patterns, medallion architecture and data integration. - Experience with identity, access control, data protection and production support. - Demonstrated ability to own technical workstreams and communicate design decisions clearly to both technical and non-technical audiences. Desirable: Event Hubs, Kafka, Purview, Power BI semantic models, dbt and relevant Azure or Fabric certifications.