Job Description
Wir prüfen und beraten unsere Mandanten mit rund 2.000 Kolleginnen und Kollegen an 10 bundesweiten Standorten und als Teil des Netzwerks Grant Thornton International mit 76.000 Mitarbeiterinnen und Mitarbeitern in 156 Ländern. Schwerpunkte unserer Arbeit sind Audit & Assurance, Tax, Advisory und Legal.
Deine Stärken. Unsere gemeinsame Wirkung.
We call our work ‘demonstrating impact'. That means an environment in which you can share your curiosity, knowledge and passion for excellence with others. Because our work demonstrates impact, Grant Thornton is one of the most successful firms for mid-market companies, start-ups and the DAX. With us you can support our clients' growth regionally, nationally and internationally, and at the same time broaden your view of the environment, society and economy.
We're growing. To complement our team we are looking for interns (m/f/d) and working students (m/f/x) in the field of Audit as soon as possible. You will be working with a team of highly skilled and supportive data scientists who work with an agile approach in their everyday tasks. Team language is English. This position is a “work from anywhere in Germany” position which requires a high degree of self-organization and excellent communication skills. The team is growing rapidly which gives you the opportunity to continue your career with us after your graduation.
As a working student / intern in Data Engineering you will work with a great team of Data Experts who are motivated to improve the quality and accuracy of information and enabling businesses to make more specific business decisions. You will work with leading partners across the organization and our clients in order to support business decisions across multiple industries and build tools to achieve the same. You would support the team regarding:
Developing our proprietary Python frameworks
- Crafting specialized Python scripts for tasks such as process mining and data analysis
- Managing coding projects in a DevOps environment
- Documenting ongoing projects for both technical and non-technical stakeholders
- Conducting ETL and post-processing of financial data from various source systems
Furthermore, you get the opportunity to learn about technical topics like:
- MS Azure Services
- Machine learning
- Technical writing
and, if you are interested in non-technical topics:
- Project management
- Financial audit
- Enrolled in a B.Sc./M.Sc. program in Computer Science, Mathematics, Business Informatics, or a related field
- Proficiency in Python development, along with experience in languages Java, C, C++, C#, TypeScript or Rust
- Fundamental understanding of processing and modeling large, complex data sets for analytical purposes
- You see the bigger picture and can break down complex topics for a non-technical audience
- You work independently and purposefully to deliver high-quality results on time and possess good communication skills in English and in German
This is a plus:
- You are interested in learning about Azure Cloud infrastructure and associated service•
- First experience, at least from the user perspective, of MS Azure, especially working with storage accounts is a plus
- First experience in working with data warehouses is a plus
- Having first experiences in data modelling and data engineering for data- and compute-intensive applications using cloud provider technology (Azure) is a big plus
- Experience with reporting tools such as PowerBI, Qlik or Tableau or data mining tools such as Knime or Alteryx or even relevant certifications are a plus
- Additional relevant experience in audit would be ideal and a big plus
- Having a basic understanding of financial data, ERP systems and accounting processes is a plus
A diverse training programme, tasks with responsibility that help you grow, and a strong team –welcome to Grant Thornton! We're already practicing active talent management, a positive feedback culture and an environment of mutual appreciation. We're constantly developing and learning about agile working, New Work and having a digital mindset.
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