AI & Data Analytics Internship, Technical Service (m/f/d) - Gigafactory Berlin-Brandenburg

What To Expect
Location: Gigafactory Berlin-Brandenburg

Duration: 6 months

Start date: September / October 2026

Time Type: Full-time

The Technical Service team is dedicated to maximizing the performance and availability of utilities and infrastructure systems, ensuring uninterrupted operations at Gigafactory Berlin. This dynamic team works tirelessly to maintain, enhance, and restore these systems through a combination of preventative and corrective maintenance strategies.

We are looking for a highly motivated and detail-oriented Data Analyst Intern to join the Maintenance Planning team. This role sits at the intersection of factory operations and data analytics: you will turn maintenance, asset, and operations data into reports, dashboards, and automation that planners, engineers, and leadership use to make decisions.

You will support strategic initiatives by preparing analytical outputs, tracking KPIs, streamlining reporting processes, and building digital tools that reduce manual effort. Working alongside analysts and maintenance professionals, you will translate business needs from Technical Service teams into functional data solutions: combining hands-on factory analytics with Python, SQL, and modern automation workflows.

What You'll Do
Reporting & analytics

• Support planning, tracking, and coordination of analytics initiatives across Technical Service and Intralogistics

• Prepare dashboards, status reports, presentations, and documentation for stakeholders

• Write and maintain SQL queries; perform data analysis and prepare decision-support briefs

• Monitor reporting timelines, data quality, and deliverables

• Build and refresh Excel exports for spare parts, preventive maintenance (PM) coverage, consumption, forecasts, and assets

Maintenance operations data

• Track KPIs for maintenance orders, PM compliance, missed work orders, and spare parts consumption

• Support asset analysis, checklist compliance, and inventory planning

• Handle ad-hoc data requests from planners and cross-functional partners

Automation & digitalization

• Translate business needs into automation solutions and internal analytics tools

• Develop Python/SQL workflows, data pipelines, and automated reporting using Git

• Support development of AI solutions such as RAG agents, automated workflows, and reusable skills for maintenance teams

• Identify automation and AI opportunities; support adoption through documentation and knowledge-sharing

Collaboration & process

• Attend meetings, capture action items, and coordinate with internal teams

• Improve analytics processes and reporting templates for efficiency and clarity

What You'll Bring

• Currently enrolled in a Bachelor's or Master's degree in Data Science, Business Informatics, Industrial Engineering, Technology & Management, Operations, or a related field

• Strong experience with SQL for data extraction, joins, aggregations, and reporting

• Proficiency in MS Office (especially Excel and PowerPoint) for structured exports, pivot tables, and stakeholder presentations

• Strong analytical and problem-solving skills with a business-first mindset

• Excellent written and verbal communication in English; German is a plus

• Strong organizational skills with exceptional attention to detail

• Proactive, reliable, and comfortable managing multiple tasks simultaneously

• Self-starter who learns quickly in a fast-paced environment

• A team player with a flexible mindset and strong sense of ownership

Preferred

• Experience with Python for data analysis, automation, and workflow integration

• Familiarity with Git and version control

• Understanding of AI/ML concepts, prompt engineering, or workflow design

• Familiarity with BI and database tools (e.g., DBeaver, Power BI, or similar)

• Demonstrated interest in building digital tools, automations, and data solutions

• Familiarity with maintenance, manufacturing, or facilities operations concepts

• Hands-on experience with at least one data or automation project used by real users — a portfolio or GitHub repository is highly recommended

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