About the position
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 DevOps 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
RequirementsRequired 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 DevOps, CI/CD pipelines, and Infrastructure-as-Code (Bicep, ARM, CLI, PowerShell, 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)
Desired Skills:
- Azure Data Factory
- Databricks
- Microsoft Fabric
- Apache Spark
Desired Qualification Level:
About The Employer:
