Celonis Data Engineer

Job Description

Celonis Data Engineer

Overall Platform & Backend Development

• Contribute to the continuous development of the backend data platform, with a strong focus on:
• Azure Databricks for data processing, transformation, and preparation
• Azure Data Factory for orchestration, ingestion, and scheduling of data pipelines
• Design, implement, and optimize end-to-end data pipelines from source systems to Celonis.
• Extend and maintain data interfaces and integrations between enterprise systems, Azure services, and Celonis.
• Adapt, extend, and maintain Celonis data models and knowledge models based on evolving business and technical requirements.
• Ensure scalability, performance, and reusability of backend and Celonis-related data solutions.

Deep Dive: Celonis & Process Mining

• Proven experience with Celonis, ideally in a Data Engineer role.
• Strong knowledge of:
• Celonis Knowledge Models
• Event-based data modeling
• Celonis PQL (Process Query Language)
• Analyses, Views, and KPIs
• Solid understanding of process mining concepts (cases, activities, variants, timestamps).

Deep Dive: Azure Data Engineering

• Hands-on experience with Azure Data Factory (ADF):
• Designing and operating ETL/ELT pipelines
• Managing triggers, schedules, and dependencies
• Error handling, monitoring, and troubleshooting pipelines
• Hands-on experience with Azure Databricks:
• Data transformations using Spark / SQL
• Building reusable data processing logic
• Preparing curated datasets for analytics and consumption
• Strong SQL skills and experience with complex joins, transformations, and aggregations.

Soft Skills

• Strong communication skills across IT, data, and business stakeholders.
• Structured, analytical, and solution-oriented mindset.
• Ability to work independently in a platform and operations-focused role.
• Willingness to document, standardize, and continuously improve solutions.

Nice to Have

• Celonis certifications (Data Engineer, Data Analyst, Knowledge Model).
• Experience with large-scale Azure-based data platforms.
• Familiarity with Agile / DevOps ways of working.
• Experience in incident, change, and release management in data platforms.