Senior DataOps Engineer / Software Engineer
Location: Munich, hybrid
About the company:
Our client is one of Europe's fastest-growing travel tech scale-ups, connecting millions of guests with holiday homes across the globe. With a team of 700+ people from 60+ countries, they move fast, think big, and build tech that genuinely matters.
For hosts looking to grow their business and guests looking for their perfect stay.
Data is at the core of everything they do.
The Team:
You'll join our newly formed Dynamic Pricing and Revenue Management team, working alongside a Data Scientist and a Data Analyst. Your shared mission: help hosts improve occupancy and earnings through smart, data-driven pricing strategies. A cross-functional setup, modern tooling, and teammates who care about impact and learning together.
The tech stack
* Data Pipelines: Airflow + dbt-core, powered by Python
* Storage & Querying: S3, Redshift, Athena, DuckDB
* ML & Model Serving: MLflow, SageMaker, deployment APIs
* Cloud & DevOps: Terraform, Docker, Jenkins, AWS EKS (Kubernetes)
* Monitoring: ELK, Grafana, Looker, OpsGenie
* Ingestion: Kafka, Airbyte, Fivetran
* AI tooling: Claude, Copilot, Codex
What you'll do
* Support model deployment and serving, help bring pricing and demand models into production, build and maintain APIs and serving infrastructure
* Build and operate production pipelines, ensuring data flows are reliable from source to model to output with proper monitoring and alerting
* Collaborate cross-functionally with Data Scientists, Analysts, and Engineering teams to turn prototypes into production-ready solutions
* Own infrastructure and tooling, set up and maintain environments, CI/CD pipelines, and the infrastructure the team depends on
* Ensure operational excellence through monitoring, automated testing, and observability across production systems
* Migrate and productionize POCs: turn experimental code into robust, maintainable Python applications
* Maintain data quality, consistency, and documentation across revenue management metrics and datasets
What you bring
* 4+ years of experience in Software Engineering, Data Engineering, DevOps, or MLOps
* Strong Python skills: you write clean, production-quality code
* Hands-on experience with CI/CD, Docker, and infrastructure-as-code (Terraform or similar)
* Familiarity with cloud platforms (AWS preferred) and deploying services in production
* Exposure to or interest in ML model deployment (MLflow, SageMaker, or similar) is a strong plus
* Curiosity about cutting-edge LLM tools and agents to boost productivity
* A proactive, ownership-driven mindset: you spot problems and drive solutions forward
What's in it for you
* Impact: work on products used by millions, where data drives decisions and your contributions are visible
* Growth: a culture built on curiosity and feedback, with personal learning budgets and a strong AI focus
* Great people: smart, international colleagues who challenge and support each other in equal measure
* Tech environment: scale-up pace with a proven business model; you build, test, and iterate continuously
* Flexibility: hybrid setup (50% in-office), plus up to 8 weeks/year working from other locations
* Perks: travel benefits, gym discounts, and regular team events across nearly 30 offices