Required skills
Job description
STACKIT published this listing. We've added our own working-student context below — what this role means for your weekly hours, take-home pay and student visa as a student in Berlin, Germany.
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Description provided by STACKIT
Join us and contribute to digital sovereignty in Europe. With us, you will work at the intersection of agility and security: You will benefit from fast decision-making processes, enjoy genuine creative freedom in your projects, and be able to build upon the stable foundation of the Schwarz Group.
Play your part in our team´s success. You will join the Article Intelligence and Finance team who is responsible for building data products and running them. We are committed to deliver high quality data products to our stakeholders and build collaboration across all teams that we work with.
Your tasks
- Orchestrate AI Coding Agents: Act as the human-in-the-loop commander for tools like Claude Code and Codex, guiding them to autonomously generate data validation scripts, build test suites, and refactor data pipelines.
- Ensure our data products are "metadata-rich by default." You will write and run automated checks to verify that live datasets perfectly match our structured JSON schemas, YAML configurations, and Markdown Business requirement documents.
- Support the engineering team by vibe coding as they rapidly prototype. When AI-assisted code breaks or data pipelines fail, you will deploy agentic workflows to automatically ingest error logs, augmented linting and rerun local tests until they pass.
- Automate architecture documentation to keep our technical maps alive. You will use AI agents to parse our codebases and automatically update our Diagram-as-Code files, ensuring our public documentation never drifts from reality.
- Audit data lineage to test and validate "Lineage as infrastructure," using agentic tools to trace data flows from raw ingestion to the final data product, making sure no data points drop off along the way.
- Solid knowledge of Python and Databricks.
- Familiarity with REST APIs, particularly FastAPI.
- Basic understanding of Data Science concepts, including Embeddings and models.
- Basic knowledge of CICD pipelines.
- Optional: SQL and experience with ETL pipelines.
- Hands-on experience with agentic terminal tools like Claude Code, Codex or equivalent AI-driven developer workflows.
- Familiarity with data serialization and documentation formats (Markdown, JSON Schema, YAML, Mermaid.js).
- Exposure to data validation principles or frameworks is a major plus.
- Ability to work flexibly and independently
- Solution-oriented mindset.
- Very good English skills - German is a plus but not a must
- Enthusiasm for collaboration, knowledge sharing and joint learning
- Openness and flexibility for diverse data related tasks.
- Proficiency in data analysis and deep diving into data quality issues.
- Experience in technical and non-technical documentation.
Working student essentials
What this Tech internship in Berlin means for you — pay rules, social contributions, and what international students should check before applying.
Weekly hours
Internships have no 20-hour cap, but a voluntary internship longer than three months generally has to pay at least the German minimum wage. Mandatory internships in your study programme are exempt.
Working student rulesSocial contributions
Mandatory internships are largely exempt from social contributions. Voluntary internships are treated like regular employment once they run long enough, so contributions usually apply.
Check your insuranceInternational students
Non-EU students can work 140 full or 280 half days per year (raised from 120/240 in March 2024). A working student contract usually fits within this — confirm the exact limits printed on your residence permit.
Studying in Germany
