Engineering Manager (Data Engineering)

TL;DR

Engineering Manager (Data Engineering): Leading the Data Engineering team to build and refine core data pipeline tools and a DataMesh-based architecture with an accent on scalability and DataOps. Focus on coaching engineers, optimizing Lakehouse architectures on AWS, and integrating AI agents into the development lifecycle.

Location: Hybrid in Munich, Germany (50% in-office time required)

Company

A fast-growing vacation rental technology company helping hosts and guests worldwide.

What you will do

• Lead and coach a team of 5 data engineers, fostering a culture of feedback and continuous learning.
• Drive technical direction and architecture decisions for core data pipelines and DataMesh implementation.
• Champion DataOps best practices, including CI/CD, automated testing, and observability.
• Collaborate with Data Analytics and Data Science teams to automate data handling best practices.
• Integrate LLM tools and AI agents to enhance team productivity.
• Translate complex technical trade-offs into plain language for non-technical stakeholders.

Requirements

• Extensive experience in Data Engineering or Software Development, ideally in startup/scale-up environments.
• Deep expertise in Lakehouse architectures on AWS and cloud-native data platforms.
• Proficiency in building scalable batch and streaming pipelines using Python, SQL, Airflow, and dbt.
• Strong knowledge of DataOps: Terraform, CI/CD, and pipeline monitoring.
• Proven technical leadership skills in goal setting and system design.
• Must be based in or be able to work hybrid in Munich, Germany.

Nice to have

• Experience with Data Governance frameworks.
• Formal people management experience.

Culture & Benefits

• Hybrid work setup with 50% in-office time and flexibility to work from other locations for up to 8 weeks a year.
• Personal learning budgets with a strong focus on AI.
• International environment with colleagues from 60+ nations.
• Travel benefits and gym discounts.