analytical Analytics Engineer

We’re looking for a highly analytical Analytics Engineer to strengthen how the team turns financial and operational data into insight. Working alongside senior analysts and business partners, you will build models, analyses, and automated data products that support smarter decisions and better performance across Finance, adoption, and GTM operations. This is a hands-on, technical role for someone who is genuinely strong with data - SQL, Python, and statistical thinking - who writes clean code, and who enjoys being close to the business and setting a higher standard of analytical and technical best practices., You’ll build scalable, automated dashboards and data products that improve the speed and accuracy of insight, helping move the team from manual reporting toward automated, self-service analytics. You’ll write clean, reproducible, version-controlled code (SQL and Python), help improve and maintain existing analytics, and make use of modern AI and agentic tooling - LLM-based assistants and coding copilots (e.g. Cursor), AI agents, and workflow automation - to accelerate work and reduce manual effort. You’ll also help maintain data quality, consistency, and governance across datasets., You’ll work closely with Finance, adoption, and GTM operations, as well as Data/Tech teams, to identify analytics opportunities and embed data-driven thinking into core business processes - acting as a connection point between the business and the data.

• 2-4 years of experience in analytics engineering, data/business analytics, BI development, or a comparable technical and analytical role
• Strong SQL skills and confidence working with large, complex datasets
• Hands-on experience with Python for data analysis, automation, and statistical/predictive modeling - a core part of the role
• Solid foundations in data modeling and/or financial modeling, forecasting, and scenario planning
• Working knowledge of statistical methods and an analytical mindset grounded in sound methodology and attention to detail
• Familiarity with software engineering best practices (version control, testing, documentation) and BI / data visualization tools
• Ability to translate data into clear insights and communicate them effectively to non-technical stakeholders
• Comfortable in a fast-paced, cross-functional environment
• Degree in Computer Science, Engineering, Mathematics, Statistics, Finance, Economics, or a related quantitative field
• Exposure to modern AI and agentic tools (LLM assistants, coding copilots such as Cursor, AI agents, prompt-based automation) and interest in applying them to analytics workflows
• Exposure to Finance or GTM/revenue operation

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. World’s leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there’s a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet.