{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/aws-eks"},"x-facet":{"type":"skill","slug":"aws-eks","display":"Aws Eks","count":1},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_8b447835-74a"},"title":"Senior DataOps Engineer - Revenue Management (all genders)","description":"<p><strong>Your future team</strong></p>\n<p>You&#39;ll be part of our new Dynamic Pricing &amp; Revenue Management team, working alongside a Data Scientist and a Data Analyst. Together, you will work towards one core goal: helping hosts improve occupancy and earnings through a smart, dynamic, and data-driven pricing strategy.</p>\n<p><strong>Our Tech Stack</strong></p>\n<ul>\n<li>Data Storage &amp; Querying: S3, Redshift (with decentralized data sharing), Athena, and DuckDB.</li>\n<li>ML &amp; Model Serving: MLflow, SageMaker, and deployment APIs for model lifecycle management.</li>\n<li>Cloud &amp; DevOps: Terraform, Docker, Jenkins, and AWS EKS (Kubernetes) for scalable, resilient systems.</li>\n<li>Monitoring: ELK, Grafana, Looker, OpsGenie, and in-house tools for full visibility.</li>\n<li>Ingestion: Kafka-based event systems and tools like Airbyte and Fivetran for smooth third-party integrations.</li>\n<li>Automation &amp; AI: Extensive use of AI tools like Claude, Copilot, and Codex.</li>\n</ul>\n<p><strong>Your role in this journey</strong></p>\n<p>As a Data Ops Engineer – Revenue Management, you&#39;ll be the engineering backbone that enables our Data Scientists to move from experimentation to production. You bridge the gap between data science models and reliable, scalable production systems.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Support model deployment and serving: help deploy pricing and demand models into production, building and maintaining APIs and serving infrastructure.</li>\n<li>Build and operate production pipelines: ensure data flows reliably from source to model to output, with proper monitoring and alerting.</li>\n<li>Collaborate cross-functionally: work closely with Data Scientists, Analysts, and Engineering teams to turn prototypes into production-ready solutions.</li>\n<li>Own infrastructure and tooling: set up and maintain the environments, CI/CD pipelines, and infrastructure that the team depends on.</li>\n<li>Ensure operational excellence by implementing monitoring, automated testing, and observability across the team&#39;s production systems.</li>\n<li>Migrate and productionize POC: turn experimental code into robust, maintainable Python applications.</li>\n<li>Ensure data quality, consistency, and documentation across revenue management metrics and datasets.</li>\n</ul>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Impact: Shape the future of travel with products used by millions of guests and thousands of hosts.</li>\n<li>Learning: Grow professionally in a culture that thrives on curiosity and feedback.</li>\n<li>Great People: Join a team of smart, motivated, and international colleagues who challenge and support each other.</li>\n<li>Technology: Work in a modern tech environment.</li>\n<li>Flexibility: Work a hybrid setup with 50% in-office time for collaboration, and spend up to 8 weeks a year from other inspiring locations.</li>\n<li>Perks on Top: Of course, we also offer travel benefits, gym discounts, and other perks to keep you energized.</li>\n</ul>\n<p><strong>Experience</strong></p>\n<ul>\n<li>4+ years of experience in Software Engineering, Data Engineering, DevOps, or MLOps.</li>\n<li>Strong hands-on skills in Python , you write clean, production-quality code.</li>\n<li>Experience with CI/CD, Docker, and infrastructure-as-code (e.g., Terraform).</li>\n<li>Familiarity with cloud platforms (AWS preferred) and deploying services in production.</li>\n<li>Exposure to or interest in ML model deployment (MLflow, SageMaker, or similar) is a strong plus.</li>\n<li>Desire to learn and use cutting-edge LLM tools and agents to improve your and the entire team&#39;s productivity.</li>\n<li>A proactive, hands-on mindset: you take ownership, spot problems, and drive solutions forward.</li>\n</ul>\n<p><strong>How to apply</strong></p>\n<p>If you&#39;re excited about this opportunity, please submit your application on our careers page!</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_8b447835-74a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Holidu Hosts GmbH","sameAs":"https://holidu.jobs.personio.com","logo":"https://logos.yubhub.co/holidu.jobs.personio.com.png"},"x-apply-url":"https://holidu.jobs.personio.com/job/2597559","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"Full-time","x-salary-range":null,"x-skills-required":["Python","CI/CD","Docker","Terraform","Cloud platforms (AWS preferred)","ML model deployment (MLflow, SageMaker, or similar)"],"x-skills-preferred":["AI tools like Claude, Copilot, and Codex","Data Storage & Querying (S3, Redshift, Athena, DuckDB)","ML & Model Serving (MLflow, SageMaker, deployment APIs)","Cloud & DevOps (Terraform, Docker, Jenkins, AWS EKS)","Monitoring (ELK, Grafana, Looker, OpsGenie, in-house tools)","Ingestion (Kafka-based event systems, Airbyte, Fivetran)"],"datePosted":"2026-04-18T22:09:42.352Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Munich, Germany"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, CI/CD, Docker, Terraform, Cloud platforms (AWS preferred), ML model deployment (MLflow, SageMaker, or similar), AI tools like Claude, Copilot, and Codex, Data Storage & Querying (S3, Redshift, Athena, DuckDB), ML & Model Serving (MLflow, SageMaker, deployment APIs), Cloud & DevOps (Terraform, Docker, Jenkins, AWS EKS), Monitoring (ELK, Grafana, Looker, OpsGenie, in-house tools), Ingestion (Kafka-based event systems, Airbyte, Fivetran)"}]}