Process Mining Developer – Mid-level

GlobalPeopleTransitions

Process Mining Developer responsible for Celonis solutions to monitor and optimize business processes. Collaborating with stakeholders and supporting advanced analytics and automation solutions.

Posted 6/8/2026full-timePécs • 🇭🇺 HungaryMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

ERPETLPythonSQL

About the role

Key responsibilities & impact

Designing, building and maintaining Celonis process intelligence solutions used to monitor and optimize critical business processes
Developing data pipelines and transformations that integrate data from multiple enterprise systems (e.g., ERP, finance, supply chain systems) into the Celonis platform
Building and maintaining real-time and analytical dashboards that provide operational insights to business stakeholders
Implementing process models using Object-Centric Process Mining (OCPM) concepts such as objects, events and relationships
Writing and optimizing complex SQL queries to model business processes, calculate KPIs and enable advanced analytics
Contributing to machine learning and AI-supported use cases within the Celonis ecosystem (e.g., anomaly detection, duplicate invoice detection)
Developing and maintaining automation workflows using Celonis ActionFlows to trigger operational actions based on process insights
Monitoring and optimizing data flows, ensuring reliable data availability and performance for dashboards and analytics
Collaborating closely with business stakeholders to understand process requirements and translate them into scalable data models and solutions
Participating in process workshops to identify relevant business objects, events and relationships within operational workflows
Supporting the full lifecycle of Celonis applications including development, release and operational maintenance
Working closely with DevOps engineers to ensure stable deployments, monitoring and operational reliability

Requirements

What you’ll need

3+ years of professional experience in data engineering, analytics engineering, BI engineering or a similar data-focused role
Strong SQL skills and experience writing complex queries involving joins, aggregations and performance optimization
Experience working with relational databases and large datasets
Solid understanding of data modeling concepts and relational data structures
Experience building data pipelines, ETL processes or analytical data models
Ability to translate business questions into data solutions and analytical models
Experience collaborating with business stakeholders and participating in requirement workshops
Practical experience using Git for version control and collaborative development
Experience working in an agile development environment
Strong analytical thinking and the ability to understand relationships between complex datasets
Growth-oriented mindset with willingness to learn new platforms and technologies
Comfortable working in an environment that includes operational responsibility; on-call participation may be required later
Nice-to-have: Experience with process mining platforms (e.g., Celonis, Signavio, UiPath)
Experience working with ERP systems such as SAP or other enterprise systems
Experience with Python for data processing or machine learning
Experience designing analytical dashboards or BI solutions
Familiarity with large-scale enterprise data environments and real-time analytics
Experience working with event-based or process-oriented data models
Understanding of supply chain, finance or purchasing business processes
AI/ML affinity: Experience working with machine learning or AI-driven analytics use cases
Interest in integrating AI capabilities into operational analytics and process monitoring
Openness to using AI-assisted development tools to improve productivity and code quality

Benefits

Comp & perks

Opportunity to work on a large-scale process intelligence platform used by thousands of users across the organization
Participation in building advanced analytics and automation solutions that directly improve business operations
Small, highly technical teams with strong ownership of solutions and architecture
Exposure to modern data engineering practices and enterprise-scale analytics environments
Opportunities to work with cutting-edge technologies such as process mining, real-time analytics and AI-driven insights
Strong support for professional growth through trainings, conferences and internal knowledge sharing
Open, collaborative working culture with close interaction between engineering and business teams
International collaboration with teams across multiple business domains
Flexible working hours with home office possibility

ATS Keywords

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Hard Skills & Tools

SQLdata engineeringanalytics engineeringBI engineeringdata pipelinesETL processesdata modelingPythonmachine learninganalytical dashboards

Soft Skills

analytical thinkingcollaborationrequirement translationgrowth-oriented mindsetoperational responsibilitycommunicationproblem-solvingadaptabilitystakeholder engagementparticipation in workshops