Staff Data Engineer (all genders)

WelcomeTechSalesCompensationOur ProductOpen PositionsHolidu CareersOpen positionsData Science / AnalyticsStaff Data Engineer (all genders)Staff Data Engineer (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 join the Data Engineering team inside our Business Intelligence department. We own the data platform end-to-end, including the infrastructure it runs on: ingesting from every source at Holidu — event tracking, RDS databases, Google Sheets, external APIs — storing it efficiently, keeping queries fast, and serving it to the analytics layer the company runs on (Looker today, built to stay tool-agnostic). We build and run that infrastructure ourselves as code with Terraform. It's a close-knit team of five (three senior engineers, a staff engineer, and a Tech Lead Manager you'll report to), working hand in hand with our analytics and data science teams to turn the tools you build into real impact.Our Tech StackThe stack is modern and Python-first:Data Pipelines: Airflow + dbt-core Data Storage & Querying: Redshift (provisioned and serverless), Athena, DuckDB, PySparkCloud & DevOps: AWS EKS (Kubernetes), Terraform, Docker, Jenkins for Continuous Integration and DeliveryIngestion: Kafka, Airbyte, FivetranMonitoring: ELK, Grafana, Looker, OpsGenie.Automation & AI: Claude, Copilot, Codex are part of the everyday workflow, not an afterthought.Your role in this journeyShape our data platform and the infrastructure it runs on end to end — from ingestion across many sources, through efficient storage and fast queries, to the serving layer the company makes decisions with.Design, build and operate reliable data pipelines that ingest data from diverse sources — streaming and batch — and land them as query-ready datasets analysts and scientists depend on.Craft the development toolchains and best practices that let analytics, data science and engineering teams build high-quality datasets on their own.Own both the architecture and the AWS bill: make the tradeoffs that keep quality and SLAs high without runaway cost, and keep pipeline performance under continuous watch.Set technical direction and shape engineering objectives together with engineering managers, researching new solutions and bringing fresh innovations to the platform.Grow the team by mentoring engineers, sharing your thinking openly, and helping recruit new talent.Your backpack is filled with8+ years of experience in Data Engineering, Software Engineering, or a similar role, ideally including time operating at a senior or staff level (for example as a Data Engineer, Analytics Engineer, or BI Engineer).Experience building and implementing Lakehouse architectures in AWS or comparable setups.Hands-on skills building batch and streaming pipelines with tools like Airflow, dbt, Redshift, Athena/Presto, Firehose, Spark, and SQL databases.Strong programming skills in Python and SQL (Java or Kotlin is a plus).Solid understanding of distributed systems and DataOps practices such as Infrastructure as Code, CI/CD for data pipelines, automated testing, monitoring and observability, and data quality management.Experience with containerization and orchestration technologies (Docker, Kubernetes/EKS).Excellent communication skills and a track record of influencing technical direction and aligning solutions with business objectives.Experience in Data Governance and enthusiasm for using LLM tools and agents to boost your team's productivity are a plus.Our adventure includesImpact:...