Description
ACT is modernizing and scaling its enterprise Data Platform, using Microsoft Fabric and technologies such as Databricks to support data integration, modelling, analytics engineering and platform architecture.
Responsibilities
•Own and continuously improve key components of ACT's Data Platform architecture and engineering standards
•Design and implement integrations for new source systems and build reliable, maintainable data pipelines
•Design, implement and document enterprise relational and dimensional data models
•Develop, optimize and operate data pipelines and orchestration using Azure Data Factory, Microsoft Fabric, Azure Functions and Logic Apps
•Plan and execute data migrations with validation, reconciliation, data-quality controls and operational monitoring
•Contribute to Data Platform modernization using Microsoft Fabric, Databricks and other modern data technologies where appropriate
•Develop and maintain trusted semantic models for scalable Power BI reporting, analytics and emerging AI use cases
•Translate business requirements into sustainable technical solutions and clearly communicate design choices to technical and non-technical stakeholders
•Demonstrate data and analytics solutions to business stakeholders and support adoption through documentation and knowledge sharing
Requirements
•Degree in Computer Science, Information Technology, Business Information Technology, Data Engineering or a comparable field, or equivalent professional experience
•5+ years of relevant data engineering experience, including substantial hands-on experience with Microsoft Azure or another major cloud platform
•Hands-on experience with modern data platforms such as Microsoft Fabric, Azure Synapse Analytics, Databricks or Snowflake
•Strong SQL skills and practical Python experience for data engineering, automation or testing
•Strong understanding of modern data architectures, including data warehouses, data lakes and Lakehouse patterns
•Strong data-modelling skills, particularly relational and dimensional modelling
•Ability to design, troubleshoot and optimize data transformations, SQL workloads and data pipelines for performance, reliability and maintainability
•Collaborative and proactive mindset, strong communication skills, ability to take ownership, continuously learn and share knowledge
Nice to have
•Familiarity with additional data-modelling approaches, Power BI, semantic models or comparable analytics and visualization technologies, Git, automated testing, CI/CD practices, relevant Azure services, streaming, event-driven architectures or real-time analytics
Conditions
No conditions stated in the posting.
