Application Guide

How to Apply for Data Engineer (f/m/d)

at Freudenberg

🏢 About Freudenberg

Freudenberg is pioneering tailor-made emission-neutral energy systems specifically for sustainable heavy-duty e-mobility, positioning itself at the forefront of the green energy transition in transportation. Working here means contributing directly to decarbonizing commercial vehicles and heavy machinery, which is a critical environmental challenge. The company's focus on custom energy solutions for specific applications makes it unique in the sustainable mobility space.

About This Role

As a Data Engineer at Freudenberg, you'll build and maintain data pipelines that power emission-neutral energy systems for heavy-duty e-mobility, directly supporting the company's mission to decarbonize transportation. This role involves designing scalable data infrastructure that integrates diverse data sources from energy systems, vehicle telematics, and operational metrics to enable data-driven decisions about energy optimization. Your work will directly impact how Freudenberg designs, monitors, and improves their sustainable energy solutions.

💡 A Day in the Life

A typical day involves designing or refining data pipelines that ingest real-time telemetry from heavy-duty electric vehicles and energy systems, collaborating with machine learning engineers to prepare datasets for predictive maintenance models, and optimizing database queries for faster analytics on energy consumption patterns. You might also implement data validation checks for new data sources and troubleshoot pipeline issues affecting the monitoring of emission-neutral energy systems.

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🎯 Who Freudenberg Is Looking For

  • Has hands-on experience building end-to-end data pipelines using Python and SQL, with specific expertise in both relational and non-relational databases relevant to IoT or telematics data
  • Demonstrates practical experience with data pipeline tools (likely Apache Airflow, Spark, or similar) and can discuss optimization strategies for real-time or near-real-time data processing
  • Shows understanding of data quality assurance systems and can provide examples of implementing validation frameworks in previous roles
  • Has experience collaborating with machine learning engineers or data scientists, particularly in energy, mobility, or IoT domains

📝 Tips for Applying to Freudenberg

1

Highlight specific experience with IoT or telematics data pipelines, as Freudenberg's heavy-duty e-mobility systems generate continuous sensor and operational data

2

Quantify your impact on pipeline optimization - mention percentage improvements in efficiency, reliability metrics, or cost savings from previous data engineering projects

3

Research Freudenberg's specific energy systems (like their battery or charging solutions) and mention how your data engineering skills could support those specific products

4

Emphasize any experience with energy data, sustainability metrics, or environmental datasets, as this aligns with their mission

5

Include examples of collaborating with cross-functional teams on data products, as the role specifically mentions working with ML engineers and data scientists

✉️ What to Emphasize in Your Cover Letter

['Your experience designing data pipelines for complex systems (especially if related to energy, mobility, or IoT)', 'Specific examples of optimizing data systems for reliability and efficiency, with measurable results', 'How your skills in Python, SQL, and database management align with building data infrastructure for emission-neutral energy systems', 'Your understanding of data quality assurance and validation in mission-critical applications']

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Freudenberg's specific e-mobility products and energy systems - understand their battery technology, charging solutions, or energy management systems
  • → The heavy-duty e-mobility market - what data challenges exist in commercial electric vehicles, fleet management, or industrial applications
  • → Freudenberg's sustainability commitments and how data supports their emission-neutral goals
  • → Recent news about Freudenberg's partnerships or projects in sustainable transportation

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Walk me through how you would design a data pipeline for real-time monitoring of battery performance in heavy-duty electric vehicles
2 Describe your experience optimizing data pipelines for scalability - what metrics do you track and what improvements have you achieved?
3 How would you ensure data quality and consistency when integrating data from multiple sources (vehicle telematics, energy systems, operational data)?
4 Discuss a time you collaborated with machine learning engineers - what data preparation and pipeline considerations were important?
5 What database solutions would you recommend for storing time-series data from vehicle sensors and energy systems, and why?
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⚠️ Common Mistakes to Avoid

  • Generic data engineering experience without specific examples relevant to IoT, telematics, or energy systems
  • Focusing only on data analysis without demonstrating strong pipeline development and optimization skills
  • Not understanding the difference between relational and non-relational database use cases for this type of role

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Freudenberg!

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