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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_ceba9e5b-250"},"title":"Senior Backend Engineer, Product and Infra","description":"<p>We&#39;re looking for a Senior Backend Engineer to build the systems and services that power our product experience. You&#39;ll own the backend infrastructure that makes our content discoverable, our features responsive, and our platform reliable at scale.</p>\n<p>Your work will directly shape what users experience: designing APIs that serve rich content, building services that handle real-time interactions, implementing content-matching systems for rights and safety, and ensuring our platform performs under load. You&#39;ll architect systems that are fast, correct, and maintainable.</p>\n<p>You&#39;ll collaborate closely with Product, ML Research, and Mobile/Web teams to ship features that matter. We use Python, Go, BigQuery, Pub/Sub, and a microservices architecture,but we care more about good judgment than specific tool experience.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Design and maintain application-level data models that organize rich content into canonical structures optimized for product features, search, and retrieval.</li>\n<li>Build high-reliability ETLs and streaming pipelines to process usage events, analytics data, behavioral signals, and application logs.</li>\n<li>Develop data services that expose unified content to the application, such as metadata access APIs, indexing workflows, and retrieval-ready representations.</li>\n<li>Implement and refine fingerprinting pipelines used for deduplication, rights attribution, safety checks, and provenance validation.</li>\n<li>Own data consistency between ingestion systems, application surfaces, metadata storage, and downstream reporting environments.</li>\n<li>Define and track key operational metrics, including latency, completeness, accuracy, and event health.</li>\n<li>Collaborate with Product teams to ensure content structures and APIs support evolving features and high-quality user experiences.</li>\n<li>Partner with Analytics and Research teams to deliver clean usage datasets for experimentation, model evaluation, reporting, and internal insights.</li>\n<li>Operate large analytical workloads in BigQuery and build reusable Dataflow/Beam components for structured processing.</li>\n<li>Improve reliability and scale by designing robust schema evolution strategies, idempotent pipelines, and well-instrumented operational flows.</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>Experience building production backend services and APIs at scale</li>\n<li>Experience building ETL/ELT pipelines, event processing systems, and structured data models for applications or analytics</li>\n<li>Strong background in data modeling, metadata systems, indexing, or building canonical representations for heterogeneous content</li>\n<li>Proficiency in Python, Go, SQL, and scalable data-processing frameworks (Dataflow/Beam, Spark, or similar)</li>\n<li>Familiarity with BigQuery or other analytical data warehouses and strong comfort optimizing large queries and schemas</li>\n<li>Experience with event-driven architectures, Pub/Sub, or Kafka-like systems</li>\n<li>Strong understanding of data quality, schema evolution, lineage, and operational reliability</li>\n<li>Ability to design pipelines that balance cost, latency, correctness, and scale</li>\n<li>Clear communication skills and an ability to collaborate closely with Product, Research, and Analytics stakeholders</li>\n</ul>\n<p><strong>Nice to Have</strong></p>\n<ul>\n<li>Experience building application-facing APIs or microservices that expose structured content</li>\n<li>Background in information retrieval, indexing systems, or search infrastructure</li>\n<li>Experience with fingerprinting, perceptual hashing, audio similarity metrics, or content-matching algorithms</li>\n<li>Familiarity with ML workflows and how downstream analytics and usage data feed back into research pipelines</li>\n<li>Understanding of batch + streaming architectures and how to blend them effectively</li>\n<li>Experience with Go, Next.js, or React Native for occasional full-stack contributions</li>\n</ul>\n<p><strong>Why Join Us</strong></p>\n<p>You will design the core data services and pipelines that power our product experience, analytics, and business operations. You’ll work on high-impact data challenges involving real-time signals, large-scale metadata systems, and cross-platform consistency. You’ll join a small, fast-moving team where you’ll shape the structure, reliability, and intelligence of our downstream data ecosystem.</p>\n<p><strong>Benefits</strong></p>\n<ul>\n<li>Highly competitive salary and equity</li>\n<li>Quarterly productivity budget</li>\n<li>Flexible time off</li>\n<li>Fantastic office location in Manhattan</li>\n<li>Productivity package, including ChatGPT Plus, Claude Code, and Copilot</li>\n<li>Top-notch private health, dental, and vision insurance for you and your dependents</li>\n<li>401(k) plan options with employer matching</li>\n<li>Concierge medical/primary care through One Medical and Rightway</li>\n<li>Mental health support from Spring Health</li>\n<li>Personalized life insurance, travel assistance, and many other perks</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_ceba9e5b-250","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Udio","sameAs":"https://www.udio.com/","logo":"https://logos.yubhub.co/udio.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/udio/jobs/4987729008","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$180,000 - $220,000","x-skills-required":["Python","Go","BigQuery","Pub/Sub","Data modeling","Metadata systems","Indexing","Canonical representations","ETL/ELT pipelines","Event processing systems","Structured data models","Scalable data-processing frameworks","Analytical data warehouses","Event-driven architectures","Kafka-like systems","Data quality","Schema evolution","Lineage","Operational reliability"],"x-skills-preferred":["Application-facing APIs","Microservices","Information retrieval","Indexing systems","Search infrastructure","Fingerprinting","Perceptual hashing","Audio similarity metrics","Content-matching algorithms","ML workflows","Batch + streaming architectures"],"datePosted":"2026-04-17T13:05:20.076Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Go, BigQuery, Pub/Sub, Data modeling, Metadata systems, Indexing, Canonical representations, ETL/ELT pipelines, Event processing systems, Structured data models, Scalable data-processing frameworks, Analytical data warehouses, Event-driven architectures, Kafka-like systems, Data quality, Schema evolution, Lineage, Operational reliability, Application-facing APIs, Microservices, Information retrieval, Indexing systems, Search infrastructure, Fingerprinting, Perceptual hashing, Audio similarity metrics, Content-matching algorithms, ML workflows, Batch + streaming architectures","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":180000,"maxValue":220000,"unitText":"YEAR"}}}]}