Job Description
We are looking for two highly skilled Platform Data Engineers to join a cutting-edge Customer Save & Open API team.

This is not your typical data role - it's a hybrid of Data Engineering and Azure Platform Engineering, where you will play a key role in building and enhancing a modern, scalable One Data Platform (ODP) aligned to enterprise-wide data strategy.

You'll be working on high-impact data products, enabling advanced analytics, real-time insights, and next-generation customer experiences.

As a Platform Data Engineer, you will:

• Translate business requirements, architecture, and data models into scalable technical solutions
• Design and build metadata-driven data ingestion pipelines using Azure Data Factory and Databricks
• Develop and maintain the Enterprise Data Warehouse (Kimball methodology)
• Build data products using Databricks and Microsoft Fabric (Lakehouse, Warehouse, Pipelines, Semantic Models)
• Implement end-to-end data engineering lifecycle within the One Data Platform (ODP)
• Engineer real-time streaming solutions using Azure Event Hubs and Stream Analytics
• Drive DevOps excellence (CI/CD, automation, infrastructure-as-code)
• Ensure data quality, testing, and performance optimization across pipelines
• Design reusable Azure templates and deployment components
• Promote data governance, security, and best practices (Purview, Unity Catalog)
• Collaborate closely with business stakeholders and cross-functional teams
• Contribute to Group Data Engineering standards, frameworks, and best practices

• 6+ years in Data Engineering / Platform Engineering
• Strong experience in Azure data ecosystem
• Hands-on expertise in Microsoft Fabric (Lakehouse, Pipelines, Semantic Models)
• Proven experience with Apache Spark for large-scale data processing
• Strong SQL skills (T-SQL) and data analysis capability

• Azure Stack:
  • Azure Data Factory
  • Azure Event Hubs
  • Azure Synapse Analytics
  • ADLS Gen2
  • Azure Stream Analytics
• Databricks (including Unity Catalog)
• ETL/ELT pipeline development (batch & real-time)
• Data modelling: Kimball & Data Vault 2.0
• Programming: Python, SQL, C#
• Data tools: Pandas, Spark

• Azure DevOps (Repos, Pipelines, CI/CD)
• Infrastructure as Code (Bicep, ARM, Azure CLI, PowerShell, Bash)
• Automated deployment pipelines

• Azure Active Directory (Authentication & Authorization)
• Data governance tools (Microsoft Purview)
• Secure data design & compliance best practices

• Experience in Banking / Financial Services
• Exposure to Open Banking technologies
• Knowledge of Data Mesh architectures

• Bachelor's degree in Computer Science or related field (or equivalent experience)
• Mandatory Azure Certification:
  • AZ-900 or DP-203 / DP-600 / DP-700
• Bonus:
  • Databricks Certifications (Fundamentals / Data Engineer Associate / Architect)