Data Analyst (f/m/x)
- Full-time
- Time Type: Full time
Company Description
At AUTODOC, our vision is to become the leading tech ecosystem in the automotive industry, seamlessly connecting all facets of the automotive aftermarket. Founded in Berlin in 2008, we have rapidly grown into Europe’s leading online retailer for vehicle spare parts and accessories. Operating in 27 countries, our diverse team of over 6,000 people from 50 nations is at the heart of our innovation and transformation journey.
We are committed to creating an environment where every team member feels a strong sense of impact, purpose, and belonging—whether they are working in our offices, warehouses, or remotely. With our headquarters in Berlin, and several offices across Europe, we are driving towards our vision with a clear focus on leveraging technology to build a sustainable future for mobility.
Join us as we accelerate towards becoming the leading tech ecosystem in the automotive world.
Catch the ride with AUTODOC!
Job Description
As a Data Analyst, your mission is to support data-driven decision-making across logistics and distribution. You will collect and interpret operational data to identify trends, pinpoint inefficiencies, and uncover improvement opportunities. By monitoring KPIs, you will help our organization enhance performance, quality, and cost optimization through clear, actionable insights.
Key responsibilities:
- Data Collection & Management: Gather and consolidate data from WMS, ERP systems, and automation platforms to maintain a robust internal database.
- Performance Monitoring: Analyze operational data to identify performance gaps and optimization opportunities within warehouse processes.
- KPI Development & Reporting: Design and maintain key performance indicators related to productivity and quality, providing regular reports to management.
- Visualization & Dashboards: Create interactive dashboards and visualizations that make performance tracking transparent and accessible.
- Operational Insights: Translate complex data into recommendations that fuel continuous improvement across the board.
- Cross-Functional Collaboration: Partner with IT, Process Engineering, and Supply Chain teams to align analytical support with business needs.
- Project Support: Provide the analytical backbone for logistics improvement projects and new automation initiatives.
Qualifications
- A degree in a technical, analytical or numerical field (Engineering, Finance, Data Analytics, etc.)
- 2–4 years of experience in data analysis, ideally within logistics, e-commerce, or supply chain environments.
- Strong skills in SQL and advanced Excel; experience with Power BI or Tableau is required.
- The ability to translate large datasets into meaningful business insights.
- A solid understanding of warehouse KPIs like throughput, productivity, and inventory accuracy.
- Fluent Polish and English skills, and the ability to present technical results to non-technical stakeholders.
- Basic knowledge of Python or R for automation and proficiency in additional languages like German will be an advantage.
Additional Information
We offer:
- Competitive salaries based on your professional experience
- Stable employment in a fast-growing international company
- A cafeteria benefits system that lets you choose from options such as life insurance, private medical care, a sports card, cinema tickets, and more
- Transportation services available for all warehouse employees
- Guaranteed 26 vacation days per calendar year, regardless of seniority
- An extra day off to celebrate your birthday
- Mental Wellbeing Program – free and confidential mental and physical health support services for you and your immediate family, covering a wide range of personal and work-related issues
- AUTODOC corporate discount for purchasing car parts at special rates for personal use
- Opportunities for advancement, further training (over 650 courses on soft and hard skills available on our e-learning platform), and coaching
- Free English, German, and Polish language classes
- Flexible working hours and a hybrid work model