Lead Process Engineer_Celonis at Absa Group Limited (Absa)

End Date: March 6, 2026

Core Accountabilities

Process Mining Leadership & Stakeholder Enablement

• Define and drive the Process Mining roadmap aligned to Home Loans strategic and operational priorities
• Establish standards for Celonis data models, KPI frameworks, and use case governance
• Lead a multidisciplinary capability spanning process analysis, data engineering, and business translation
• Act as the senior interface between Operations, Credit, Risk, Finance, and IT

Process Intelligence for Advanced Analytics & AI

• Structure and expose high-quality process-level data to support predictive and prescriptive analytical models Provide process-grounded data structures to support AI and machine learning initiatives (e.g., approval likelihood prediction, delay and fallout risk indicators, intelligent case routing, workload optimisation) Collaborate with Data Science and AI teams to ensure models reflect true end-to-end process dynamics and are tied to measurable business outcomes

Celonis Delivery, Operational Enablement & Value Realisation

• Oversee end-to-end Celonis deployments from data sourcing through digital twin creation, opportunity identification, value framing, and value tracking across operational, financial, customer, and risk dimensions Translate process insights into targeted interventions that improve cycle times, reduce rework, optimise cost-to-serve, and enhance service quality Drive Celonis literacy and embed process mining adoption and performance disciplines across Home Loans business units
• Drive executive visibility of process performance and value delivered

Qualifications

• Minimum 10 years’ experience driving operational efficiency through structured improvement methodologies and data-driven insight within complex high, high volume environments such as financial services
• Bachelor’s degree in Engineering, Business, Data Science, or a related field preferred
• Professional certifications in Lean, Six Sigma, or related disciplines are advantageous
• Data/Technical certifications in analytics or cloud SaaS platforms are advantageous

Required Experience & Core Competencies

• Extensive experience leading cross-functional continuous improvement initiatives using Lean, Six Sigma, or similar structured problem-solving approaches
• Experience working with large operational datasets and applying analytics in operational contexts (e.g., forecasting volumes, predicting delays, identifying error patterns, prioritising workloads) to uncover performance drivers, bottlenecks, and root causes
• Strong ability to translate operational challenges into data-led analysis and actionable insights, identifying, quantifying, and tracking value opportunities including cost reduction, productivity gains, capacity release, and risk reduction
• Skilled in defining performance baselines, control measures, and sustainable monitoring frameworks using operational KPIs, and linking process behaviour to financial and risk outcomes
• Proven ability to build a culture of data-driven performance management, influencing stakeholders across Operations, Technology, Risk, and Finance, and driving adoption of improved processes and performance disciplines
• Experience collaborating with data science, analytics, or AI teams to operationalise models and embed analytical outputs into workflows and decision-making routines

Education

• Master's Degree: Information Technology