Data engineer (analytics & data platform)

We are looking for an experienced Mid-to-Senior Data Engineer to play a key role in the design and delivery of a modern analytics and reporting platform within a complex, multi-system business environment. In this role, you will lead the development of scalable data solutions, build robust data pipelines, and design business-critical data models that transform fragmented operational data into actionable insights. Working closely with stakeholders across Operations, Support, Quality Assurance, Workforce Management, and CRM functions, you will consolidate data from multiple source systems into a unified analytics ecosystem powered by Microsoft Fabric. This is a highly autonomous position suited to someone who thrives in complex environments, takes ownership of technical delivery, and can confidently make architectural and engineering decisions. You will play a pivotal role in shaping the organisation's data strategy, enabling reliable reporting, advanced analytics, and data-driven decision‑making across the business. The ideal candidate will combine strong technical expertise with excellent stakeholder engagement skills, demonstrating the ability to navigate ambiguity, manage multiple data sources, and drive successful outcomes within a dynamic project landscape.

Key Responsibilities Design, develop, and maintain scalable data pipelines and ingestion frameworks to support enterprise reporting and analytics needs. Integrate and consolidate data from a wide range of Saa S applications, operational systems, and external data sources. Transform and model raw data into high‑quality, business‑ready datasets that enable accurate reporting and data‑driven decision‑making. Architect, implement, and manage Lakehouse and Data Warehouse solutions within Microsoft Fabric. Develop robust semantic models and curated datasets that serve as the foundation for Power BI reporting and analytics. Collaborate closely with business stakeholders to gather requirements, define key metrics and KPIs, and translate business needs into scalable data solutions. Identify, investigate, and resolve data quality, integrity, reconciliation, and consistency issues across multiple systems. Provide technical leadership and make sound architectural decisions to ensure scalable, maintainable, and future‑proof solutions. Monitor, troubleshoot, and optimise data pipelines to improve performance, reliability, and operational efficiency. Champion best practices in data engineering, governance, modelling, security, and analytics architecture. Required Qualifications & Experience Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline, or equivalent practical experience. 5-7 years of hands‑on experience in Data Engineering, Analytics Engineering, or similar data‑focused roles. Proven experience delivering production‑grade solutions using Microsoft Fabric, including Lakehouse, Warehouse, Dataflows, Pipelines, and Semantic Models. Advanced SQL skills, including query optimisation, performance tuning, and dimensional data modelling. Strong Python development experience for data transformation, automation, orchestration, and systems integration. Solid understanding of modern data platform architectures, including Data Warehousing and Lakehouse methodologies. Experience integrating and managing data from REST APIs, Saa S applications, and third‑party systems. Hands‑on experience designing and consuming semantic models within Power BI environments. Proficiency with Git‑based source control and CI/CD practices for data and analytics projects. Strong analytical and problem‑solving abilities, with exceptional attention to detail. Excellent communication and stakeholder management skills, with the ability to translate business requirements into technical solutions and clearly articulate design trade‑offs. Comfortable working independently in fast‑moving environments, navigating ambiguity, and balancing technical excellence with practical delivery outcomes. Preferred Experience Exposure to Azure Data Factory, Azure Synapse Analytics, and/or Databricks. Experience implementing data quality, observability, monitoring, and reconciliation frameworks. Familiarity with operational Saa S platforms such as Zendesk, Hub Spot, Zoho, Intercom, Aircall, or similar customer service and CRM solutions. Knowledge of modern analytics engineering tools and practices, including dbt and related technologies. Interest or experience in AI‑driven analytics, automation, and intelligent data workflows. Understanding of data governance, privacy, security, and compliance best practices within regulated environments. Technology Environment

Data & Analytics Platform Microsoft Fabric (Lakehouse, Warehouse, Dataflows, Pipelines, Semantic Models)

Cloud & Data Services Azure Data Factory (Preferred) Azure Synapse Analytics (Preferred) Databricks (Preferred)

Development Languages SQL Python

Reporting & Visualisation Power BI

Data Modelling Dimensional Modelling Lakehouse Architecture Semantic Modelling

Integration Technologies REST APIs Saa S Connectors (Zendesk, Hub Spot, Zoho, Intercom, Aircall, and similar platforms)

Dev Ops & Collaboration Git Git Hub CI/CD Pipelines VS Code Slack What's on Offer

We provide a competitive remuneration package, flexible working arrangements, and a collaborative, low‑ego culture that values continuous learning, innovation, and work‑life balance. Team members benefit from ongoing professional development opportunities, including access to training and certification budgets to support career growth. While Cape Town is the preferred location for this role, we are open to remote or hybrid working arrangements across South Africa for the right candidate. This position is ideally suited to a full‑time professional, although contract‑to‑permanent opportunities may also be considered. #J-18808-Ljbffr