Senior Data Engineer | South Africa | Permanent Build the data backbone that powers smarter logistics decisions. Own complex pipelines that turn operational data into real‑time insight across the supply chain. This role sits at the core of a Business Intelligence environment, responsible for designing, building, and maintaining a scalable data infrastructure that supports reporting, advanced analytics, and automation. You will work with high‑volume operational and supply chain data, ensuring secure, reliable, and timely access for analytics, optimisation, and decision‑making across the logistics value chain. Working closely with BI, analytics, and operational stakeholders, you will integrate multiple data sources, improve data quality, and continuously optimise performance. The environment is fast‑paced and operationally critical, requiring strong problem‑solving skills, attention to detail, and the ability to work under pressure. Our client operates in a complex, regulated logistics environment, supporting critical supply chain operations across South Africa. The organisation is data‑driven, performance‑focused, and committed to using analytics and automation to improve efficiency, visibility, and compliance across its network. What You’ll Do Design, build, and maintain robust ELT pipelines with high availability and low latency Integrate data across ERP, WMS, TMS, and IoT platforms Manage and optimise data lake and data warehouse environments Develop, optimise, and maintain advanced SQL transformations and pipelines Ensure high standards of data quality, validation, and governance Collaborate with BI and data science teams to deliver trusted datasets Automate recurring data processes to reduce manual effort Investigate data issues, perform root cause analysis, and implement permanent fixes Maintain clear documentation and support data cataloguing initiatives Support data security, access controls, and compliance requirements What You Bring Degree in Computer Science or a related field 3–5 years’ experience in data engineering, ideally within logistics or supply chain environments Strong experience with ELT/ETL tools such as Azure Data Factory, SSIS, or Apache Airflow Advanced SQL expertise and proficiency in Python or a similar scripting language Solid understanding of data modelling and data warehousing concepts Experience working with cloud data platforms (Azure, AWS, or GCP) Familiarity with version control and CI/CD practices for data products Strong analytical thinking, problem‑solving ability, and attention to detail What Success Looks Like Reliable, well‑documented data pipelines with minimal failures High data quality, consistency, and availability across systems Improved query performance and reduced data latency Faster onboarding of new data sources and datasets Measurable reduction in manual effort through automation Trusted datasets that enable accurate reporting and analytics #J-18808-Ljbffr