Data Engineer

ESSENTIAL ROLES & RESPONSIBILITIES * Identify and understand customer data-centric use cases within regulated financial services environments * Design and implement data ingestion, processing, and transformation pipelines on Azure * Build and maintain data pipelines for cleaning, normalisation, enrichment, and preparation * Apply appropriate data modelling techniques and architecture patterns, with a strong focus on medallion architecture * Orchestrate, monitor, and optimise Azure Databricks jobs and Azure Data Factory pipelines across development, UAT, and production environments * Operationalise workflows developed by analysts and data scientists * Support customers in adopting Azure data, analytics, and machine learning services GOVERNANCE & REPORTING * Maintain accurate documentation of data pipelines, schemas, transformations, and deployment processes * Support data governance initiatives including lineage, metadata management, and access control TECHNOLOGY STACK (AZURE) Data Engineering & Analytics: * Azure Databricks (development, UAT, and production) * Azure Data Factory * Azure Synapse Analytics (where applicable) Databases: * Microsoft SQL Server / Azure SQL Database (primary platforms) * PostgreSQL (limited use) * MySQL (limited use) Security & Governance: * Role-based access control (RBAC) * Data encryption and key management * Audit logging and monitoring CRITICAL COMPETENCIES – TECHNICAL FIT Essential: * Strong SQL skills * Programming experience with Python and/or Scala * Hands-on experience with Azure-based data platforms * Experience designing, building, and maintaining data pipelines * Strong understanding of data modelling (relational and analytical), including medallion architecture * Experience orchestrating and optimising Databricks and Data Factory workloads * Experience using CI/CD pipelines for data and analytics solutions * Strong awareness of security, networking best practices, GDPR, and PII handling Desirable: * Experience with Azure Databricks in production environments * Familiarity with Azure Machine Learning and AI services SHIFT & WORKING PATTERN * Standard business hours, with participation in an on-call rota as required * Occasional weekend engineering coverage will be required, typically limited to a small number of planned weekends per year to support business continuity, resilience testing, or disaster recovery activities