Engineering Manager - Data Engineering (all genders)

WelcomeTechSalesCompensationOur ProductOpen PositionsHolidu CareersOpen positionsData Science / AnalyticsEngineering Manager - Data Engineering (all genders)Engineering Manager - Data Engineering (all genders)Munich, GermanyShare jobHolidu is one of the world’s fastest-growing vacation rental technology companies. Our mission is to make booking and hosting holiday homes free of doubt and full of joy, by helping hosts generate more bookings with less work and helping guests find a holiday home they truly enjoy. Our team of 700 colleagues from 60+ nations shares a passion for tech, an ambition for constant improvement, and a relentless drive to bring the best experience to more than 40k vacation rental hosts and 4 million annual guests.Your future teamYou'll lead the Data Engineering team in the Business Intelligence department, which consists of 5 data engineers. This team is responsible for creating, maintaining, and refining the core data pipeline tools, as well as supporting several end-user pipelines. Your team will assist the organization in addressing all its data needs and, simultaneously, enhance the data platform with new capabilities and refactoringYou will work closely with the data analytics and data science teams to enable them to leverage further the tools you have built, as well as develop and automate best practices for handling data on our platform.You will take on the responsibility to create an enabling DataMesh-based approach to support different teams in leveraging the data to create data-driven applications.Our Tech StackData Pipelines: Airflow + dbt-core, powered by Python.Data Storage & Querying: Redshift, Athena, DuckDB.Cloud & DevOps: AWS EKS (Kubernetes), Terraform, Docker, Jenkins.Ingestion: Kafka, Airbyte, Fivetran.Monitoring: ELK, Grafana, Looker, OpsGenie.Automation & AI: Claude, Copilot, Codex.Your role in this journeyThis role is equal parts people leadership and hands-on technical contribution. You won't just manage — you'll shape how the team works, roll up your sleeves when it counts, and set the technical standard by example. Here's what that looks like day to day:Lead and grow your team. Coach 6 data engineers, create a culture of feedback and continuous learning, and recruit the people who will strengthen the team.Stay hands-on. You'll contribute directly to architecture decisions, code reviews, and complex technical challenges.Own the technical direction. Partner with Data Analysts, Data Scientists and stakeholders to set clear goals, prioritize the right work, and make sure the team builds things that actually matter.Drive engineering quality. Champion DataOps best practices — CI/CD for data pipelines, automated testing, monitoring, observability, and data quality standards across the board.Unblock and enable. Remove friction, resolve ambiguity, and make sure your engineers can do their best work without unnecessary overhead.Connect engineering to the business. Translate complex technical trade-offs into plain language for non-technical stakeholders and align solutions with real business needs.Push the stack forward. Evaluate new technologies with cost, velocity, and reliability in mind — and give your team the space to do the same.Embed AI into how your team works. Champion the use of LLM tools and AI agents to improve productivity and keep the team ahead of the curve.Your backpack is filled withExtensive hands-on experience as a Data Engineer, Software Developer, or in a closely related technical field, ideally in a fast-paced startup or scale-up environment.Deep experience with Lakehouse architectures on AWS and cloud-native data platformsExperience in building scalable batch and streaming pipeline architectures using tools like Airflow, dbt, Redshift, Athena, Spark, or similar.Strong command of Python and SQL.Solid understanding of DataOps principles: Infrastructure as Code (Terraform), CI/CD, automated testing, pipeline monitoring, and data quality managementHands-on experience...