Job Description
A software engineer role focused on designing and developing a data generation framework that creates realistic, complex synthetic event-log datasets to power product demonstrations and support sales and marketing efforts at Celonis.
Key Responsibilities
- Design, develop, and maintain a data generation framework for creating synthetic event-log datasets.
- Model complex business processes and simulate real-world scenarios to generate realistic data.
- Implement logic to generate datasets that reflect specified target metrics and KPIs.
- Apply statistical and simulation techniques to introduce realism and variability into generated data.
- Collaborate with cross-functional teams to understand requirements and translate them into data generation features.
- Manage the entire project lifecycle from requirements gathering to documentation and deployment.
- Provide feedback for product improvements and anticipate future needs to support upcoming product releases.
Requirements
- Proficiency in Python with 2-4 years of professional software development experience.
- Proven experience in building data models, running simulations, or applying statistical modeling to solve complex problems, including working with distributions, state machines, and stochastic processes.
- Experience querying and manipulating large datasets using SQL.
- Ability to effectively collaborate with both technical and non-technical stakeholders to gather requirements and explain solutions.
- Self-starter mentality with the ability to drive projects forward independently and make critical design decisions.
- Ability to operate with a high degree of autonomy, be disciplined, and self-motivated.
- Experience in designing and building programmatic models that simulate real-world business processes such as Order-to-Cash, Procure-to-Pay, Lead-to-Opportunity.
- Experience implementing core logic that allows users to specify target metrics (e.g., average case duration, rework rate, total invoice value) and generate datasets reflecting these outputs.
- Knowledge of applying statistical methods and simulation techniques to introduce realistic noise, variations, and complexities into generated data.
- Experience managing the entire project lifecycle from requirements gathering and design to implementation, testing, and documentation.
- Excellent communication skills to collaborate with technical and non-technical stakeholders.
- Ability to design and develop a robust and user-friendly data generation framework using modern software engineering practices.
Benefits & Perks
generous PTO
hybrid working options
company equity RSUs
comprehensive benefits
extensive parental leave
dedicated volunteer days
gym subsidies
counseling and well-being programs
community and support through inclusion and belonging programs
clear career paths and internal mobility
dedicated learning program and mentorship opportunities
opportunities to work with leading process mining technology
international team collaboration
empowered environment with autonomous teams
Ready to Apply?
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