Data Engineer (Cloud Data Architecture / Pipelines / API Integration / Python)

We are seeking an experienced Data Engineer to design and implement a modern, scalable data architecture that integrates multiple systems into a unified analytics environment. The goal is to centralise data from accounting, CRM, fitness management, and marketing platforms to support automated reporting and advanced analysis. Responsibilities: Design and develop data pipelines to extract, transform, and load data from multiple cloud and on-premise sources. Build secure and reliable data storage architecture to serve as a central data hub for reporting and analytics. Develop and maintain API integrations where available, and set up scheduled ingestion for non-API data such as CSV, Excel, or JSON files. Use Python for custom integrations, transformation logic, and automation workflows. Prepare and structure data for reporting, following best practices in modelling, performance, and governance. Implement data validation, monitoring, and error handling processes. Provide clear technical documentation covering data sources, transformations, and refresh logic. Requirements: Proven experience designing and maintaining modern cloud-based data environments. Strong knowledge of ETL design, data modelling, and workflow automation. Hands-on experience with Python for API integration and data transformation. Solid understanding of data governance, performance optimisation, and security. Ability to communicate effectively with business and technical stakeholders. Nice to Have: Experience integrating data from accounting, CRM, or marketing systems. Familiarity with business intelligence environments and reporting best practices. Deliverables: Centralised, scalable data architecture for analytics and reporting. Automated data pipelines and transformation workflows. Documented and reusable framework to support future reporting requirements. Apply tot his job