Process Mining Engineering Consultant

Role Overview

As a Process Mining Engineering Consultant, you will focus on the monitoring, support, execution, development, and implementation of process mining, task mining, and execution solutions. The role emphasizes technical execution and development, including data pipeline optimization, high-quality data integration, and contribution to AI-driven solutions that enhance process automation and analytics. You will work closely with the Center of Excellence (CoE) team to drive process efficiencies and operational improvements.

Key Responsibilities

• Execute process mining initiatives by monitoring, supporting, developing, maintaining, and optimizing data pipelines, models, dashboards, and execution applications.
• Collaborate with the Center of Excellence team to implement structured knowledge layers and integrate business context into process insights.
• Translate business requirements into detailed technical implementations aligned with global best practices.
• Develop and maintain high-quality data extraction, transformation, and integration pipelines, ensuring accuracy, consistency, and reliability.
• Troubleshoot, optimize, and maintain process mining solutions to ensure efficient execution and timely delivery of insights.
• Support the implementation of AI-driven techniques (predictive analytics, NLP, machine learning) to enhance automation and decision-making.
• Work within Agile development methodologies, participating in sprints, backlog refinement, and collaborative development activities.
• Ensure compliance with global data governance and security standards when integrating enterprise applications and external data sources.
• Support knowledge transfer initiatives by maintaining documentation, training materials, and best practice repositories.

Skills & Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, Business Administration, Mathematics, or a related field.
• Experience in process improvement, technology consulting, or software implementation, with a strong focus on data engineering, process mining, and automation.
• Hands-on experience in at least one business domain (Finance, Procurement, Supply Chain, HR, Customer Service) with understanding of workflows, KPIs, and optimization opportunities.

Technical Skills

• Process Mining: Hands-on experience with platforms such as Celonis or Signavio, including dashboards, execution apps, and automation workflows.
• Data Engineering & Integration: Experience with ETL processes and data warehousing concepts.
• Enterprise Applications: Familiarity with SAP (S/4HANA, ECC), Ariba, ServiceNow, Salesforce, including data structures and integration points.
• Cloud & Big Data: Experience with cloud platforms (AWS, Google Cloud, Azure, Salesforce Data Cloud) and Databricks.
• Knowledge Layers & Graphs: Exposure to knowledge layers/knowledge graphs and tools such as Neo4j, Amazon Neptune, or Stardog.
• AI-Driven Techniques: Experience supporting predictive analytics, NLP, and machine learning use cases.
• Data Analytics: Strong skills in SQL, Python, or R for data manipulation and analysis.
• BI & Visualization: Proficiency in Power BI, Tableau, or similar tools.
• Version Control & Collaboration: Experience using GitHub for version control, collaboration, and CI/CD.
• Automation Technologies: Knowledge of RPA and experience identifying automation opportunities.

Process Optimization & Agile Development

• Exposure to Agile methodologies (Scrum, Kanban) with practical experience using Azure DevOps for backlog management and CI/CD pipelines.
• Understanding of BPM methodologies such as KAIZEN or Lean Six Sigma.
• Familiarity with project management approaches (Agile, Scrum, Waterfall).
• Experience with change management practices to support process transitions.

Desirable Extras

• Process Mining Certifications (e.g., Celonis Certified Data Engineer – CCDE).
• Databricks Certified Data Engineer Associate.