Process Mining Developer (mid-level)

Your responsibilities:

• 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

The knowledge I own:

• 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

The offer that would convince me:

• 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

Online application:

Please use our online application and attach your English resume.

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