Senior DataOps Engineer

Senior DataOps Engineer

München Vollzeit 63000 - 77000 € / Jahr (geschätzt) Hybrid
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Auf einen Blick

  • Aufgaben: Entwickle und betreibe Produktionsdatenpipelines und verwalte Preismodell-APIs.
  • Unternehmen: Schnell wachsendes internationales Technologieunternehmen in der Reisebranche.
  • Vorteile: Flexible Arbeitsmodelle, Reisevorteile und regelmäßige Teamevents.
  • Weitere Informationen: Werde Teil eines dynamischen, internationalen Teams, das Lernen und Innovation schätzt.
  • Warum dieser Job: Gestalte Systeme, die Millionen von Gästen weltweit unterstützen und innoviere mit modernster Technologie.
  • Qualifikationen: 4+ Jahre Erfahrung in Software Engineering oder Data Engineering und starke Python-Kenntnisse.

Das prognostizierte Gehalt liegt zwischen 63000 - 77000 € pro Jahr.

Our client is a rapidly growing international technology company in the travel and vacation rental industry.

They develop innovative solutions that simplify the way travelers book holiday homes and help hosts grow their businesses efficiently.

With a diverse team of over 700 colleagues from more than 60 nationalities, the organization combines the agility of a fast-scaling tech company with the stability of an established business model.

Data-driven decision-making, continuous improvement, and modern technology are at the core of the company culture, creating an environment where employees are encouraged to take ownership, innovate, and make a measurable impact.

As the business continues to expand globally, the company is investing heavily in its Revenue Management and Data Engineering capabilities.

They are now looking for a Senior Data Ops Engineer / Software Engineer – Revenue Management to join their team and help transform experimental models into reliable, scalable, and impactful production systems.

  • Tech Stack
  • Data Pipelines

Data Storage & Querying : S3, Redshift (with decentralized data sharing), Athena, and Duck DB.

ML & Model Serving : MLflow, Sage Maker, and deployment APIs for model lifecycle management.

Cloud & Dev Ops : Terraform, Docker, Jenkins, and AWS EKS (Kubernetes) for scalable, resilient systems.

Monitoring : ELK, Grafana, Looker, Ops Genie, and in-house tools for full visibility.

Ingestion : Kafka-based event systems and tools like Airbyte and Fivetran for smooth third-party integrations.

Automation & AI : Extensive use of AI tools like Claude, Copilot, and Codex.

  • Main Tasks
  • Deploy and maintain pricing and demand models in production, building APIs and serving infrastructure for reliable operation.
  • Develop and operate production-grade data pipelines, ensuring smooth flow from data sources to models and outputs with robust monitoring and alerting.
  • Collaborate closely with Data Scientists, Analysts, and Engineering teams to turn prototypes into production-ready solutions.
  • Own and maintain infrastructure, CI/CD pipelines, and supporting tooling for the Revenue Management team.
  • Implement operational best practices including monitoring, automated testing, and observability across production systems.
  • Convert proof-of-concept and experimental code into robust, maintainable Python applications.
  • Ensure high data quality, consistency, and proper documentation for all Revenue Management metrics and datasets.
  • Actively leverage AI and modern tooling to optimize workflows and team productivity.

Requirements

  • 4+ years of experience in Software Engineering, Data Engineering, Dev Ops, or MLOps.
  • Strong hands-on experience in Python and ability to write clean, production-ready code.
  • Experience with CI/CD, Docker, and infrastructure-as-code tools such as Terraform.
  • Familiarity with cloud platforms, preferably AWS, and deploying services in production environments.
  • Exposure to or interest in ML model deployment platforms like MLflow, Sage Maker, or similar.
  • Motivated to explore and adopt modern AI tools and LLM agents to enhance productivity.
  • Proactive, hands-on mindset with strong ownership, problem-solving skills, and ability to drive solutions forward.
  • Strong collaboration and communication skills to work effectively in cross-functional teams.

Benefits

  • Opportunity to shape Revenue Management systems used by thousands of hosts and millions of guests worldwide.
  • Work in a modern, data-driven technology environment with cutting-edge tools and frameworks.
  • Collaborate with an international, motivated team that values learning, innovation, and impact.
  • Professional growth through mentorship, learning budgets, and a focus on AI and emerging technologies.
  • Flexible hybrid working model with 50% in-office collaboration.
  • Up to 8 weeks per year to work remotely from inspiring locations.
  • Competitive benefits including travel perks, wellness and gym discounts, and regular team and company events.
  • Be part of a culture that celebrates wins, encourages curiosity, and balances ambition with a fun and human-centered environment.

Senior DataOps Engineer Arbeitgeber: Zero to One search

Unser Kunde ist einer der am schnellsten wachsenden Fintech-Unternehmen in Deutschland und bietet eine moderne mobile Banking-Plattform, die innovative Finanzprodukte mit einem herausragenden digitalen Kundenerlebnis kombiniert. Die Unternehmenskultur fördert ein agiles und dynamisches Arbeitsumfeld, in dem Mitarbeiter die Möglichkeit haben, Schlüsselprozesse aktiv zu gestalten und ihre Karriere langfristig zu entwickeln. Mit einem modernen Büro im Herzen von Frankfurt und zahlreichen Zusatzleistungen wie einem öffentlichen Verkehrsticket, einem Fahrrad-Leasing-Programm und regelmäßigen Teamevents ist dies ein attraktiver Arbeitgeber für alle, die in einem zukunftsorientierten Sektor arbeiten möchten.

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Kontaktdaten:

Zero to One search Recruiting-Team

Wir glauben, dass du diese Fähigkeiten brauchst, um Senior DataOps Engineer mit Bravour zu bestehen

Python
CI/CD
Docker
Terraform
AWS
MLflow
SageMaker