Analytics Engineer

Data & AIposted 12d ago

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.

The Team:

You'll join the Data & Transformation (DAT) team, part of the Strategic Intelligence & Business Partner pillar. DAT is responsible for elevating data-driven decision-making across Finance and our go-to-market functions. This is an engineering role embedded close to the business: you'll write real code and build data products, but you'll also sit with the stakeholders you serve. We're raising the technical and analytical bar of the function — moving from descriptive reporting toward predictive, prescriptive, and AI-augmented insights — and we want people who help push that standard higher.

The Role:

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.

The work you’ll do:

Analytics & Business Support

You'll partner with stakeholders across Finance and GTM operations to translate business questions into structured analyses and clear, well-reasoned recommendations. You'll help build the narratives and visuals that make complex data understandable, and contribute to the analytics priorities the team sets each quarter.

Advanced Analytics & Modeling

You'll build and maintain robust data and financial models, forecasting logic, and scenario analyses to support planning and decision-making. You'll develop and refine KPIs and performance metrics that give clear visibility into business drivers, and apply statistical methods and predictive modeling to anticipate trends and surface risks and opportunities early. We expect a high level of analytical rigor: sound methodology, clean assumptions, and results you can defend.

Data Products, Automation & AI

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.

Cross-functional Collaboration

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.

The qualifications you need:

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 operations data

What Celonis can offer you:

Pioneer Innovation: Work with the global leader in Process Mining and the Process Intelligence Graph to shape the future of AI-driven business operations.
Ownership from Day 1: Every full-time "Celonaut" is an owner, receiving Restricted Stock Units (RSUs) and merit-based refresh grants.
Unrivaled Family Support: Benefit from our inclusive parental leave policy—24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers, available from your first day of employment.
Work-Life Integration: Enjoy Unlimited PTO (in applicable regions) and generous PTO globally, as well as a flexible hybrid work model that balances remote focus with vibrant office collaboration.
Continuous Growth: Elevate your skills through our 70-20-10 learning framework, mentorship programs, and access to a dedicated learning platform.
Holistic Well-being: Prioritize your health with subsidized Wellhub memberships, mental health counseling, and dedicated "Wellness Weeks" that prioritize work/life balance.
Drive Sustainability: Participate in annual Impact Days, where you receive paid time off to volunteer for community and environmental causes with your local office, or virtually.
Global Inclusion & Belonging: Find community through our Inclusion Think Tank and participate in our annual Inclusion Days, ensuring every voice is heard and valued.
Value-Driven Impact: Join a mission-led organization where our core values—Live for Customer Value, The Best Team Wins, We Own It, and Earth Is Our Future—drive every decision.

About Us:

Celonis is the trusted platform to industrialize Enterprise AI, empowering organizations to analyze, design, and operate AI-driven processes. The Celonis Platform is powered by the Celonis Context Model, which combines process data, business knowledge, and intelligence to create a living digital twin of the enterprise that AI can understand — turning AI’s operational blind spots into operational clarity. Industry-leading companies around the world trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. Celonis is headquartered in Munich, Germany, and New York City, USA, with more than 20 offices worldwide.

Get familiar with the Celonis Process Intelligence Platform by watching this video.

Celonis Inclusion Statement:

At Celonis, we believe our people make us who we are and that “The Best Team Wins”. We know that the best teams are made up of people who bring different perspectives to the table. And when everyone feels included, able to speak up and knows their voice is heard - that's when creativity and innovation happen.

Your Privacy:

Any information you submit to Celonis as part of your application will be processed in accordance with Celonis’ Accessibility and Candidate Notices

By submitting this application, you confirm that you agree to the storing and processing of your personal data by Celonis as described in our Privacy Notice for the Application and Hiring Process.

Please be aware of common job offer scams, impersonators and frauds. Learn more here.