Senior data engineer (azure / microsoft fabric) - banking sector
Summary
Senior data engineer builds and optimizes Azure-based data pipelines and warehouses for a bank using Microsoft Fabric, Databricks, and Azure Data Factory.
We are seeking a highly skilled Senior Data Engineer to join a dynamic team within a leading banking environment. This role is ideal for someone passionate about building scalable, high-performance data platforms and delivering robust data solutions that drive business value.
You will play a key role in designing, developing, and optimising modern data architectures, working with cutting-edge technologies such as Microsoft Fabric, Azure Data Factory, and Databricks . Key Responsibilities Translate business, architectural, and data requirements into scalable technical solutions Design and build metadata-driven data ingestion pipelines using Azure Data Factory and Databricks Develop and maintain enterprise-grade Data Warehouses (Kimball methodology) Build and model data products using Databricks and Microsoft Fabric Implement end-to-end data engineering solutions using IDX templates into ODP (One Data Platform) Drive Dev Ops best practices , including CI/CD and automation Perform unit testing, integration testing, and debugging to ensure high-quality deployments Design and manage Azure infrastructure components and templates Develop and maintain documentation, governance standards, and best practices Collaborate with business stakeholders to understand and deliver on data requirements Apply data governance and engineering standards to ensure high-quality, secure data products Participate actively in data engineering and modelling communities of practice Support operational processes and shared team responsibilities Requirements Required Skills & Experience 6+ years' experience as a Data Engineer / Platform Engineer Strong experience with Microsoft Fabric (Lakehouse, Warehouses, Pipelines, Notebooks, Semantic Models) Hands‑on experience with Azure Data Factory, Databricks, and Azure Synapse Analytics Expertise in Apache Spark for large-scale data processing Strong SQL skills (T-SQL) and data analysis capabilities Experience with real-time data streaming (Azure Event Hubs, Stream Analytics) Solid understanding of ETL design and optimisation Experience with data governance tools (Unity Catalog, Microsoft Purview) Knowledge of Data Warehouse methodologies (Kimball, Data Vault 2.0) Proficiency in Python, C#, and SQL Experience with Azure Dev Ops , CI/CD pipelines, and Infrastructure-as-Code (Bicep, ARM, CLI, Power Shell, Bash) Understanding of data mesh architectures Familiarity with Azure AD security, authentication, and authorization Agile delivery experience Qualifications Bachelor's Degree in Computer Science or related field (or equivalent experience) Mandatory: One or more Microsoft Azure certifications (AZ-900, DP-203, DP-600, or DP-700) #J-18808-Ljbffr