Midrand: Power BI Industrial Engineer

Job Purpose To support data‑driven decision-making by analysing operational and business data, building dashboards, and identifying process improvements. This role combines data analytics with industrial engineering methodology to improve efficiency, reduce waste, and enhance overall business performance in Logistics. Key Responsibilities Data Analysis & Modelling Analyse operational, production, supply chain, and business datasets. Build performance models, forecasts, and basic statistical analyses. Conduct root‑cause analysis using data-driven insights. Identify patterns, gaps, and efficiency opportunities. Reporting & Visualisation Build and maintain dashboards in Power BI / Tableau / Qlik . Develop automated reporting processes. Present insights clearly to management and cross‑functional teams. Track and measure KPIs and operational performance. Process Improvement (Industrial Engineering Focus) Apply Lean, Six Sigma, workflow mapping, and IE tools to analyse processes. Assist in designing and implementing improvement solutions. Support optimisation projects such as throughput improvement, cost reduction, layout optimisation, etc. Conduct time & motion studies where necessary. Data Management & Governance Clean, validate, and maintain data quality. Collaborate with IT/data teams to improve data structures. Document datasets, dashboards, and analytical processes. Cross-Functional Collaboration Work closely with Operations, Finance, Supply Chain, and IT. Support project teams with quantitative analysis. Contribute to continuous improvement initiatives and action planning. Minimum Qualifications Bachelors Degree in Industrial Engineering (essential). Additional qualifications in Data Analytics, Business Intelligence, or Statistics (advantageous). Certifications in Power BI, SQL, Lean Six Sigma, Python are beneficial. Required Skills & Competencies Technical Skills Strong analytical and problem‑solving ability. Advanced Excel. Power BI / Tableau / Qlik dashboarding experience. SQL for querying and data extraction. Python or R exposure (beneficial). Industrial engineering tools (Lean, Six Sigma, mapping, optimisation). Soft Skills Excellent communication and presentation skills. Ability to convert complex data into business‑friendly insights. Stakeholder engagement ability at operational and management level. High attention to detail and accuracy. Ability to manage multiple projects simultaneously. Experience Requirements (25 Years) 25 years experience as a Data Analyst, BI Analyst, Process Analyst, or Industrial Engineer. Experience working with operational or supply chain data preferred. Demonstrated experience building dashboards and analytical reports. Exposure to process improvement or continuous improvement initiatives. Experience in manufacturing, logistics, operations, or service environments is advantageous. 6. Key Performance Indicators Accuracy, reliability, and quality of reports and insights. Improvement in operational KPIs due to analytical recommendations. Quality and adoption of dashboards and reporting tools. Successful execution of improvement projects. Stakeholder satisfaction and cross‑department collaboration.