Job Description
A software engineer role focused on designing and developing a data generation framework to create realistic, complex synthetic event-log datasets for product demonstrations, enabling visualization and analysis of enterprise business processes within the Celonis platform.
Key Responsibilities
- Design, develop, and maintain a data generation framework for creating complex, synthetic event-log datasets.
- Model real-world business processes and simulate their variations to generate realistic data.
- Implement logic to generate datasets that meet 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 incorporate feedback into data generation tools.
- Manage the entire project lifecycle from requirements gathering to documentation and deployment.
- Build tools that support product demonstrations and automate demo processes.
- Anticipate future product needs and develop supporting tools aligned with upcoming 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 operate with a high degree of autonomy, drive projects forward independently, and make critical design decisions.
- Ability to model complex business processes such as Order-to-Cash, Procure-to-Pay, Lead-to-Opportunity, and their variations.
- Implement core logic that allows users to specify target metrics (e.g., average case duration of 5.2 days, rework rate of 15%, total invoice value of 1.2B) and generate datasets that reflect these outputs when processed by the Celonis platform.
- Apply statistical methods and simulation techniques to introduce realistic noise, variations, and complexities into generated data to make it indistinguishable from real-world customer data.
- Manage the entire project lifecycle from requirements gathering and design to implementation, testing, and documentation.
- Design and build a robust and user-friendly data generation framework using modern software engineering practices.
- Develop programmatic models that simulate real-world business processes and their variations.
- Implement logic to reverse-engineer from metrics to generate datasets that meet specified targets.
- Collaborate closely with value engineering, product management, and product marketing teams to understand their needs and translate them into features for data generation tools.
- Anticipate future product releases and build tools to support them, timed to coincide with their release dates.
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 programs and mentorship opportunities
opportunity to work with leading process mining technology
international and collaborative work environment
Ready to Apply?
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