This position is available to applicants from both the United Kingdom and Latin America (LATAM)
Job Summary:
We are looking for a seasoned UI Path Process Mining Consultant with 15–20 years of experience in the manufacturing industry. The ideal candidate will have a deep understanding of manufacturing operations, extensive experience in process optimization, and hands-on expertise with UI Path Process Mining.
Key Responsibilities:
Lead comprehensive Process Mining initiatives using UI Path across manufacturing business functions.
Partner with stakeholders across operations, quality, supply chain, and IT to map and analyze critical processes.
Integrate various enterprise systems, especially QAD ERP, MES, and PLM platforms, with the Process Mining tool.
Interpret large volumes of data to identify bottlenecks, redundancies, and areas suitable for automation.
Create visual dashboards, KPIs, and actionable reports to support executive decision-making.
Collaborate with CoE teams to translate mined insights into automated process pipelines.
Ensure compliance with audit and governance frameworks through detailed documentation and process transparency.
Guide junior team members and act as a domain expert in manufacturing and process transformation.
Required Skills & Qualifications:
Minimum 3–5 years of hands-on experience with UI Path Process Mining or similar tools (e.g., Celonis, Signavio).
Proven experience with QAD ERP and understanding of its data structures and process flows.
Deep knowledge of manufacturing business processes – including production, quality, logistics, and supply chain.
Strong skills in SQL, data modeling, and business intelligence/reporting tools.
Excellent communication skills with the ability to influence cross-functional stakeholders.
Preferred Qualifications:
UI Path certifications in Process Mining, Automation, or RPA.
Exposure to Lean, Six Sigma, or other process improvement frameworks.
Experience leading digital transformation projects in a manufacturing environment.
Familiarity with integration platforms and data lakes.
