Intern IT Aftersales - Data Engineering (Mandatory Internship)

Tätigkeitsbereich: IT/Telekommunikation
Fachabteilung: Customer Analytics & BI
Gesellschaft: Mercedes-Benz AG
Standort: Stuttgart
Startdatum: 16.08.2026
Veröffentlichungsdatum: 16.08.2026
Stellennummer: MER000420S
Arbeitszeit: Vollzeit

Aufgaben

Are you a tech-savvy individual with a passion for AI, data engineering, and problem-solving? Do you want to gather hands-on experience at a globally renowned company that is pushing the boundaries of automotive innovation? Would you like to work on a strategically critical system that is about to go live and directly contribute to its robustness, reliability, and innovation? Then join our After-Sales IT department at Mercedes-Benz!

Who we are and what we do:

We in the Team Customer Analytics and BI aim to put our customers at the center of our work in order to deliver a seamless customer journey and to provide them with the best-fit products and services they need. We do so by building customer-centric data products through connecting various data sources, such as vehicle diagnostics, as well as applying machine learning models to gain valuable insights. Furthermore, by harnessing data from our global workshop network, we continuously improve our customers' service experience, make strategic business decisions, and effectively steer various After-Sales processes. To make this happen, we work in self-organized, interdisciplinary, and agile teams across IT and business departments.

Things you will do:

Investigate and resolve data inconsistencies across complex end-to-end data pipelines

Automate complex analytics across large datasets to validate outputs and identify anomalies or inconsistencies

Debug pipeline failures and improve overall pipeline robustness

Design and implement existing requirements and new features for the product

Collaborate with international cross-functional teams to understand, implement, and troubleshoot features of a complex data system

Skills you will develop depending on your interests:

AI-assisted coding: by developing and debugging with help of an integrated AI-agent, you will learn to scale up your own performance and become your own development team

Data Analysis Skills: Through investigating inconsistencies and validating outputs, you'll sharpen your ability to evaluate and interpret complex datasets

Problem-Solving Abilities: By debugging pipelines and conducting root cause analyses, you'll develop a structured approach to solving real-world data issues

Data Engineering Expertise: By developing and debugging end-to-end pipelines, you'll gain a deep understanding of ETL processes, dependencies, and data flow architectures

Reliability Engineering Mindset: You will learn how to improve data quality, fault tolerance, and system robustness in production-critical environments

Experience with modern cloud data services and architectures

Technical Communication: Through documentation and collaboration across teams, you will strengthen your ability to clearly communicate technical findings and solutions

The activity can begin from August 2026.

Qualifikationen

Currently pursuing a bachelor's or master’s degree in Computer Science, Information

Technology, Data Engineering, Data Science, or a related field with a focus on data or software engineering

Strong English proficiency

Strong foundation in data engineering, backend engineering, or data science

Experience working with end-to-end data pipelines, including dependencies and failure points

Ability to understand and reason about complex data flows and transformations

Strong proficiency in Python

Working knowledge of PySpark for data transformations

Basic understanding of SQL

Solid practical experience with Git (version control, branching, debugging changes)

Hands-on experience using AI-assisted coding or debugging tools (GitHub Copilot or similar)

Clear understanding of ETL/ELT concepts and data pipeline architecture

Basic understanding of AWS data services (e.g., Lambda, Glue, S3)

Strong, structured debugging approach (hypothesis-driven, methodical isolation)

Proven ability to perform root cause analysis on data inconsistencies and t issues across pipelines

Understanding of fault tolerance and resilience in data pipelines

Communication and interpersonal skills, with the ability to work well in a team as well as independently

It helps if you are interested / have some background in:

Experience with monitoring and alerting tools (data or system-level)

Experience with CI/CD pipelines and infrastructure automation (e.g., GitHub Actions, Pulumi)

Hands-on experience with database management (schema design, performance, debugging)

Experience with data migration or go-live projects

Experience automating repetitive operational tasks

Please note that your internship at this location must be mandatory.

Additional Information:

We look forward to receiving your online application, including a resume, cover letter, certificates, current certificate of enrollment stating your semester, proof of mandatory internship if applicable, and proof of the standard period of study. Please remember to mark your documents as "relevant for this application" in the online form and observe the maximum file size of 5 MB.

You can find further information on the hiring criteriahere .

Severely disabled applicants and applicants with equivalent status are welcome! The representative for severely disabled employees (sbv-zentrale@mercedes-benz.com) will gladly support you in the application process.

HR Services will be happy to help you with any questions you may have about the application process. You can reach us by email atmyhrservice@mercedes-benz.comor by phone at 0711/17-99000 (Mon-Fri 10am-12pm & 1pm-3pm).

Benefits

• Barriere­frei­heit
• Kantine, Café
• Kinder­betreuung
• Coaching
• Betriebs­arzt
• Mobilitäts­angebote
• Mit­arbeiter Events
• Mit­arbeiter­rabatte möglich
• Mit­arbeiter­beteili­gung möglich
• Mit­arbeiter­handy möglich
• Essens­zulagen
• Gesund­heits­maß­nahmen
• Hybrides Arbeiten möglich
• Betrieb­liche Alters­ver­sorgung
• Park­platz
• Gute An­bindung
• Flexible Arbeits­zeit möglich

Kontakt

Manuel Bauer
Email: manuel.b.bauer@mercedes-benz.com
Am Wallgraben 114 Haus B
70565 Stuttgart