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      Stenon

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      Senior Data Engineer Interview

      20 Jan 2025
      Anonymous employee
      Berlin
      Accepted offer
      Positive experience
      Average interview

      Application

      I applied online. The process took 2 weeks. I interviewed at Stenon (Berlin) in Dec 2024

      Interview

      The interview process was structured, transparent, and engaging. It consisted of: 1. An initial call with the CTO to discuss my background and the company’s vision. 2. A second call with the CTO focusing on technical and problem-solving questions to evaluate my approach to challenges. 3. A home task followed by a presentation to the team, showcasing my proposed solution and answering their questions. 4. A follow-up session with a Data Engineer to understand the tasks I’d be handling. 5. A final conversation with the CEO to discuss overall fit and company culture. 6. A fast decision after the weekend, including a call with the CTO to address open topics like salary, vacations, and equipment. The process gave me a great opportunity to meet the team, gain insights into the work culture, and understand the challenges I’d be tackling. I appreciated the focus on my thought process, the "why and how" of problem-solving, and tool selection. Overall, I had a very positive experience and felt the team was genuinely interested in finding the right fit both professionally and personally.

      Interview questions [1]

      Question 1

      - Erzählen Sie etwas über Ihren beruflichen Hintergrund. - Wie würden Sie Datenpipelines für IoT-Geräte entwerfen und implementieren? - Welche Schritte unternehmen Sie, um die Arbeit eines Data-Science-Teams effizient zu organisieren (z. B. Model Registry, Training, Deployment)? - Wie gehen Sie an komplexe Probleme heran und wählen die passenden Tools aus? - Können Sie ein Beispiel geben, bei dem Sie ein bestehendes Problem mit einer kreativen Lösung adressiert haben? - Wie stellen Sie die Datenqualität in einer Data-Pipeline sicher? - Haben Sie Erfahrung mit bestimmten Technologien wie MLFlow, Airflow, oder AWS?
      Answer question

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