{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/llmops"},"x-facet":{"type":"skill","slug":"llmops","display":"LLMOps","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_11ec86c6-270"},"title":"Senior Data Engineer","description":"<p>You&#39;ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won&#39;t just contribute. You&#39;ll make things happen–fast.</p>\n<p>We are looking for a highly skilled Senior Data Engineer to become part of our core Data &amp; AI Engineering team. In this pivotal role, you will be responsible for designing and expanding enterprise-level data infrastructure that enables ZoomInfo&#39;s internal teams to interact with data comprehensively,extracting, exploring, analyzing, and generating insights,through various platforms using ZI&#39;s internal chat agent</p>\n<p>The ideal candidate has a strong background in big data processing, pipeline orchestration, and data modeling, with a proven track record of delivering scalable and high-quality data solutions in fast-paced, data-centric product environments. Given the dynamic nature of emerging technologies, this role requires an individual who excels at exploration and embraces continuous learning as core responsibilities.</p>\n<p>You&#39;ll constantly research and implement innovative solutions while integrating vast, diverse data sources into our AI applications, including our industry-leading LLM-powered systems</p>\n<ul>\n<li>Design, develop, and maintain high-performance, product-centric data pipelines using Airflow, DBT, and Python.</li>\n<li>Architect and optimize the massive-scale data warehouse and lakehouse that serves as our single source of truth for all customer data, primarily using Snowflake.</li>\n<li>Lead the integration of diverse structured and unstructured data sources (e.g., web data, third-party APIs) into our data ecosystem, ensuring high-quality and reliable ingestion.</li>\n<li>Implement and enforce Model Context Protocol (MCP) or similar architectures to feed accurate and contextual data into our LLM-powered products for applications like Retrieval Augmented Generation (RAG) and advanced search.</li>\n<li>Collaborate with ML engineers, data scientists, and product managers to translate business needs into scalable data solutions that directly enhance customer value.</li>\n<li>Define, monitor, and enforce data quality SLAs across all pipelines and products, ensuring data accuracy and lineage are a top priority.</li>\n<li>Mentor and coach junior engineers, promoting best practices in code quality, data architecture, and operational excellence.</li>\n<li>Participate in architectural decisions and long-term strategy planning for our enterprise-wide data infrastructure, with a focus on cost, performance, and reliability.</li>\n</ul>\n<ul>\n<li>Expert-level SQL for building performant, scalable queries and transformations on massive datasets.</li>\n<li>Strong Python programming skills with a focus on distributed computing, data manipulation, and building robust APIs.</li>\n<li>Production-level experience for large-scale batch and streaming data processing.</li>\n<li>Hands-on experience with DBT (Data Build Tool) for advanced data modeling and transformations in a modern data stack.</li>\n<li>Deep knowledge of Snowflake data warehouse design, optimization, and cost modeling.</li>\n<li>Experience implementing Model Context Protocol (MCP) or similar architectures to feed structured and unstructured data into LLM-powered systems.</li>\n<li>Strong understanding of data architecture concepts, including data lakes, event-driven architectures (e.g., Kafka), ETL/ELT, and data mesh.</li>\n<li>Proficiency with cloud platforms (GCP and/or AWS) and infrastructure as code (e.g., Terraform).</li>\n</ul>\n<p>Nice to Have:</p>\n<ul>\n<li>Familiarity with LLMOps, LangChain, or RAG (Retrieval Augmented Generation) pipelines.</li>\n<li>Experience with building embedding models or pipelines for Named Entity Recognition (NER).</li>\n<li>Knowledge of data cataloging tools (e.g., OpenLIneage, etc.) and lineage tracking.</li>\n<li>Familiarity with other distributed systems and databases (e.g., DynamoDB, Flink).</li>\n</ul>\n<p>Required Non-Technical Skills:</p>\n<ul>\n<li>Excellent communication skills – ability to explain complex technical concepts to both engineering teams and non-technical stakeholders.</li>\n<li>Strategic &amp; Product-Oriented Thinking – can translate business objectives and customer needs into scalable, high-impact data solutions.</li>\n<li>Leadership &amp; Mentorship – experience guiding and uplifting engineering teams to achieve their full potential.</li>\n<li>Stakeholder Management – able to collaborate effectively across departments (Product, Engineering, Sales, Compliance).</li>\n<li>Agility &amp; Adaptability – thrives in ambiguous, evolving environments and can rapidly prototype and iterate on solutions.</li>\n<li>Strong documentation habits and ability to evangelize best practices across the organization.</li>\n</ul>\n<p>Qualifications:</p>\n<ul>\n<li>Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.</li>\n<li>8+ years of progressive experience in data engineering, with a track record of leadership and impact.</li>\n<li>Demonstrated experience in implementing or scaling data infrastructure for a data-centric product company.</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_11ec86c6-270","directApply":true,"hiringOrganization":{"@type":"Organization","name":"ZoomInfo","sameAs":"https://www.zoominfo.com/","logo":"https://logos.yubhub.co/zoominfo.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/zoominfo/jobs/8509474002?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"Competitive salary and benefits package","x-skills-required":["SQL","Python","Airflow","DBT","Snowflake","Model Context Protocol","LLM-powered systems","data architecture","cloud platforms","infrastructure as code"],"x-skills-preferred":["LLMOps","LangChain","RAG","Named Entity Recognition","data cataloging tools","lineage tracking","distributed systems","databases"],"datePosted":"2026-04-24T12:18:45.901Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Toronto, Ontario, Canada"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"SQL, Python, Airflow, DBT, Snowflake, Model Context Protocol, LLM-powered systems, data architecture, cloud platforms, infrastructure as code, LLMOps, LangChain, RAG, Named Entity Recognition, data cataloging tools, lineage tracking, distributed systems, databases"}]}