Data Engineer | AI & Analytics

Requirements

• Own pipeline implementation end-to-end: environment and connectivity setup, build, validation, deployment and go-live support
• Translate business rules and AI-generated prototypes from consulting teams into validated, production-ready pipelines
• Integrate diverse sources: ERP systems, databases, external data, non-standard Excel and flat files
• Define and automate tests including schema checks, row-count and value reconciliations, and failure alerts
• Review SQL data models and database design; recommend improvements for scalability, performance and maintainability
• Manage development and production deployments; monitor and troubleshoot pipelines in production
• Work directly with client IT teams on connectivity, access, security and deployment requirements
• 4–7 years of relevant experience in data engineering
• Strong hands-on experience with Azure Data Factory (ADF) (mandatory)Hands-on experience with Azure Self-Hosted Integration Runtime (SHIR) (mandatory)
• Strong Python skills, including data validation, reconciliation and source-to-target parity matching
• Strong grounding in SQL data modelling and database design fundamentals
• Experience with Azure SQL and Microsoft Entra ID (preferred)