Data and ML Specialist (f/m/d)

E.ON Digital Technology GmbH | Permanent | Part or Full time 


E.ON Digital Technology (EDT) manages and implements with around 2,200 employees the digital transformation of E.ON. EDT is headquartered in Hanover, Germany and is internationally present across all E.ON locations.

E.ON is one of the strongest operators of European energy networks and energy-related infrastructure, as well as a provider of advanced customer solutions for more than 50 million customers. With a total of over 75,000 employees we are represented in 15 countries. By focusing on two sustainable growth areas and with the acquisition of innogy, we are ideally positioned to drive the energy transition in Germany and Europe.

At E.ON diversity matters. We welcome all people and are convinced that differences make us stronger. Become part of our inclusive and diverse company culture!

We are looking for a Data and ML Specialist (f/m/d) to join our E.ON Digital Technology GmbH team.



Do you love data and technology? Do you think we all need to become more sustainable? Are you ready to drive and boost the green energy transition? Then this is the right job for you. Your energy shapes the future!

Being aware of the enormous responsibility we have for our customers, our assets, and the environment, we are analyzing and developing solutions, utilizing advanced big data and machine learning technologies to provide the best service, improve the efficiency and make things smarter, better, and cleaner.


Your Impact

  • Team-up with our scientists, business and infrastructure experts to design data solutions that have global impact and scale to all E.ON countries

  • Evaluate new data technologies to efficiently integrate latest machine learning solutions and analytical modules into operational cloud services

  • Increase efficiency and time-to-market by implementing re-usable generic data models,  data transformations, and cloud architecture blueprints

  • Enhance analytics capabilities by combining huge diverse sets of structured, unstructured, batch and streaming data

  • Ensure high quality and stability through agile processes and peer code reviews

  • Share your ideas and convince to go new ways



  • You have a degree in Computer Science or a related technical discipline or other significant work experience

  • You have hands-on coding experience to process huge data sets, manipulate, aggregate, and join data preferably in Python

  • Ideally you have already experience with data transformations in Spark and Databricks

  • You know how to implement pipelines in Azure Data Factory, and how to efficiently deploy infrastructure as a code

  • You have designed  data models, data ingestion procedures and queries

  • Working with git and CI/CD flows is preferred by you. Knowledge of Azure DevOps is considered as a plus

  • Ideally you already have knowledge of Machine Learning frameworks like MLlib, scikit-learn, Azure ML, etc.

  • Excellent writing and communication skills, considering varying levels of precision and matching the audience

  • Fluent in English; German language skills are seen as a plus



  • Company pension scheme and company insurance worldwide

  • Exclusive employee discounts and subsidized canteen

  • Family Service (help with finding kinder garden, elder care, holiday entertainment)

  • 38 h working week and 30 leave days

  • Home Office Option in consultation with the team

  • Parental leave for mothers and fathers is perfectly normal

  • Flex time account and 100% paid travel time including business travel (>50km) in first class by train

  • Additional benefits for people with a disability

  • Very good working atmosphere (informal "du", colloquial atmosphere, very international teams)


Do you have questions?
For further information please contact Sarah Klammer,,


What you need to know:
Contract type: Permanent
Working time: Part or Full time
Company: E.ON Digital Technology GmbH
Location: Berlin, München, Hannover, Würzburg, Essen
Function area: IT/Digital

Meet us here


Berlin, DE München, DE Hannover, DE Würzburg, DE Essen, DE