{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/resource-management-infrastructure"},"x-facet":{"type":"skill","slug":"resource-management-infrastructure","display":"Resource Management Infrastructure","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_e3241178-753"},"title":"Engineering Manager - Platform Reliability","description":"<p>At Databricks, we enable data teams to solve the world&#39;s toughest problems by building and running the world&#39;s best data and AI infrastructure platform. The Lakebase Platform Reliability team&#39;s footprint spans multiple stacks, systems, and stakeholders.</p>\n<p>You&#39;ll contribute to the wider platform mission: building resource management infrastructure, reliable distributed services, and internal tools that help Databricks engineers operate confidently across clouds and environments.</p>\n<p>Responsibilities:</p>\n<ul>\n<li>Hire great engineers to build an outstanding team.</li>\n<li>Support engineers in their career development by providing clear feedback and develop engineering leaders.</li>\n<li>Ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence).</li>\n<li>Work with engineering and product leadership to build a long-term roadmap.</li>\n<li>Coordinate execution and collaborate across teams to unblock cross-cutting projects.</li>\n<li>Resource management infrastructure powering the big data and machine learning workloads on the Databricks platform in a scalable, secure, and cloud-agnostic way.</li>\n<li>Lead development of reliable, scalable services and client libraries that work with massive amounts of data on the cloud, across geographic regions and Cloud providers.</li>\n<li>Build tools to allow Databricks engineers to operate their services across different clouds and environments.</li>\n<li>Build services, products and infrastructure at the intersection of machine learning and distributed systems.</li>\n</ul>\n<p>What we look for:</p>\n<ul>\n<li>5+ years of Engineering experience and 2+ years of Engineering Management experience.</li>\n<li>Experience with large-scale distributed services and the processes around testing, monitoring, and SLAs.</li>\n<li>Ability to align multiple stakeholders on competing priorities.</li>\n<li>Able to balance short-term delivery against long-term stability.</li>\n<li>BS (or higher) in Computer Science, or a related field.</li>\n</ul>\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_e3241178-753","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Databricks","sameAs":"https://databricks.com","logo":"https://logos.yubhub.co/databricks.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/databricks/jobs/8476543002","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["large-scale distributed services","testing","monitoring","SLAs","resource management infrastructure","reliable distributed services","internal tools","cloud-agnostic","machine learning","distributed systems"],"x-skills-preferred":[],"datePosted":"2026-04-18T15:51:04.537Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"London, United Kingdom"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"large-scale distributed services, testing, monitoring, SLAs, resource management infrastructure, reliable distributed services, internal tools, cloud-agnostic, machine learning, distributed systems"}]}