The opportunity
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity.
What you'll do
Design, build and maintain resilient data infrastructure that gathers data: from a variety of sources - enterprise systems, communication tools, product telemetry and observability systems. Ensure the continuous and reliable flow of data needed to support all the product analytics activities.
Build a scalable platform which can support Celonis as a Digital Twin and: apply the Celonis Solutions internally to "Drink your own Champagne"
Continuously engage in refining data engineering processes to ensure data: accuracy, consistency, and integrity through continuous audit and review
Conduct in-depth analytic investigations to find answers to business: questions or support making the case for product and/or engineering ideas The qualifications you need: Bachelor's degree or equivalent with a strong focus on Mathematics, Computer Science, or Data Science. Master's or PhD preferred.
+ years relevant experience as an Analytics Engineer / Data Engineer or: similar, partnering with product, engineering or growth teams at a Saas or enterprise software company
Experience with data engineering building analytic data repositories: leveraging data sources from cloud billing, product telemetry and observability systems
What they're looking for
- Extensive experience building a scalable data stack within Databricks in an Enterprise Context.
- Hands-on experience working with multi-cloud setup across GCP, AWS and Azure will be a huge plus.
- Outcome-oriented with strong decision-making skills and the ability to: prioritize multiple objectives while meeting aggressive deadlines.
- Have excellent written and verbal communication skills; exceptional attention to detail.
