Lead Process Mining Engineer

Role: Lead Process Mining Engineer

Location: Remote - USA

Mode: Contract

Job Description:

As a Process Mining Engineering Consultant, you will focus by monitoring, support, execution, development, and implementation of process mining, task mining, and execution solutions. You will be responsible for optimizing data pipelines, ensuring high-quality data integration, and contributing to AI-driven solutions that enhance process automation and analytics. Your role will emphasize technical execution, development, and implementation, ensuring seamless collaboration with the Center of Excellence team to drive process efficiencies and operational improvements.

Key Responsibilities:

• Execute process mining initiatives by monitor, support, developing, maintaining, and optimizing data pipelines, models, dashboards, and execution apps
• Work closely with the Center of Excellence team to implement structured knowledge layers, ensuring seamless integration of 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, ensuring efficient execution and timely delivery of insights.
• Support the implementation of AI-driven techniques (e.g., predictive analytics, NLP, machine learning) to enhance automation and decision-making in process mining.
• Adhere to Agile development methodologies, participating in sprints, backlog refinement, and collaborative development efforts.
• Ensure compliance with global data governance and security standards while integrating enterprise applications and external data sources into process mining solutions.
• Support knowledge transfer initiatives by maintaining documentation, training materials, and best practices repositories.

Skills & Qualifications:

Education & Experience:

• Bachelor s or Master s degree in Computer Science, Information Systems, Business Administration, Mathematics, or a related field.
• X + years of 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 (e.g., Finance, Procurement, Supply Chain, HR, or Customer Service) with an understanding of process workflows, KPIs, and optimization opportunities.

Technical Skills:

• Process Mining Expertise: Hands-on experience with leading process mining platforms (e.g., Celonis, Signavio), with a focus on implementing dashboards, execution apps, and automation workflows.
• Data Engineering & Integration: Familiarity with data integration techniques and tools, including ETL (Extract, Transform, Load) processes and data warehousing concepts.
• Enterprise Applications & Data Structures: Familiarity with business applications such as SAP (S/4HANA, ECC), Ariba, ServiceNow, Salesforce, including data structures, tables, and integration points.
• Cloud & Big Data Processing: Experience with cloud platforms (e.g., AWS, Google Cloud, Azure, Salesforce Data Cloud) and Databricks for large-scale data processing and analytics.
• Knowledge Layers & Graphs: Exposure to Knowledge Layers/Knowledge Graphs and tools like Neo4j, Amazon Neptune, Stardog for structured business context integration.
• AI-Driven Techniques: Experience supporting AI-powered process mining solutions, including predictive analytics, NLP, and machine learning.
• Data Analytics Skills: Strong capabilities in data analytics, including experience with SQL, Python, or R for data manipulation and analysis.
• BI & Visualization: Proficiency in Power BI, Tableau, or similar tools for effective data visualization and reporting.
• Version Control & Collaboration: Experience using GitHub for version control, collaboration, and CI/CD processes.
• Automation Technologies: Knowledge of automation tools and technologies, such as Robotic Process Automation (RPA), and experience in identifying automation opportunities.

Process Optimization & Agile Development:

• Exposure to Agile methodologies (Scrum, Kanban) and practical experience with Azure DevOps for backlog management and CI/CD pipelines.
• Understanding of Business Process Management (BPM) methodologies such as KAIZEN or Lean Six Sigma.
• Project Management: Familiarity with project management methodologies (e.g., Agile, Scrum, Waterfall) to ensure effective project execution.
• Change Management: Experience in change management practices and methodologies to support successful transitions to new processes.

Soft Skills & Collaboration:

• Team Collaboration: Ability to work collaboratively with the Process Mining CoE and other stakeholders, fostering collaboration and shared goals.
• Problem-Solving Skills: Strong analytical and problem-solving abilities to address complex process challenges and develop innovative solutions.
• Communication Skills: Excellent verbal and written communication skills to facilitate stakeholder engagement and present findings effectively.
• Adaptability: Willingness to adapt to changing project requirements and priorities while maintaining focus on delivering on time high-quality results.

Desirable Extras

• Process Mining Certifications: Celonis Certified Data Engineer (CCDE)

Databricks Certified Data Engineer Associate