{"schemaVersion":"jobsearcher.job.v1","id":"15cf7dbfb9fe12b65eec9529","url":"https://jobsearcher.com/jobs/15cf7dbfb9fe12b65eec9529","canonicalUrl":"https://jobsearcher.com/jobs/15cf7dbfb9fe12b65eec9529","title":"Data Engineer","description":"About Infactory\nWe’re Infactory. Our mission is to further AI innovation through facts and trust. Our fact platform powers AI applications for businesses that depend on accuracy. Whether our customers are building chatbots, search tools, knowledge management systems, or bleeding-edge Gen AI technology, our solution ensures responses are not just intelligent, but factual and useful.\nSome of our values:\nFacts are at the center of everything we build. We hold ourselves to the highest standards of definitive accuracy.\nWe develop technology that builds and restores trust.\nWe’re not riding the AI wave–we’re reshaping it. We don’t do hype.\nWe make great products that are easy, trustworthy and useful.\nYou day-to-day will often change, but it may include:\nGet to know our customer’s data: Work directly with customers and data partners to gain a deep understanding of their data contents and structures. Act as a liaison between technical teams and data providers, translating business needs into technical requirements.\nManage data integrations: Write detailed specifications for integrating new data sources into our existing tech stack. Develop robust and efficient code to implement these integrations, ensuring smooth data flow and compatibility.\nBuild smart data models: You'll use our frameworks to create queries that find valuable facts in different types of data. These data models will be the foundation for smart designs and speedy processing.\nWork across the technology stack: Use NoSQL datastores, like Apache Cassandra and Google Bigtable. Leverage data analytic tools such as Apache Spark and Apache Kafka to process and analyze large datasets.\nQualifications\nNote: These are guidelines, not hard requirements! If you think you’d be a good fit, please apply.\nDegree in Statistics, Data Science, Computer Science, Mathematics,, Engineering, or a related quantitative field.\n3-5+ years work experience on data engineering or similar\nExperience working directly with customers or stakeholders to gather data requirements\nProficiency in at least one programming language commonly used in data engineering (e.g., C++, Python, Java, Scala)\nStrong experience with NoSQL databases\nHands-on experience with big data processing tools, especially Apache Spark and Apache Kafka\nSolid understanding of data modeling principles and best practices\nFamiliarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and their data services\nCompensation and Benefits\nSan Francisco Bay Area/Hybrid preferred, remote considered.\n$120k-150k with equity in an early-stage startup\nCompetitive benefits\n20 days PTO + paid holidays + unlimited sick leave\n401K\nHealthcare\nCompensation Range: $120K - $150K","company":"Infactory","rawCompany":"infactory","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-04-12T20:37:22.057Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"About Infactory\nWe’re Infactory. Our mission is to further AI innovation through facts and trust. Our fact platform powers AI applications for businesses that depend on accuracy. Whether our customers are building chatbots, search tools, knowledge management systems, or bleeding-edge Gen AI technology, our solution ensures responses are not just intelligent, but factual and useful.\nSome of our values:\nFacts are at the center of everything we build. We hold ourselves to the highest standards of definitive accuracy.\nWe develop technology that builds and restores trust.\nWe’re not riding the AI wave–we’re reshaping it. We don’t do hype.\nWe make great products that are easy, trustworthy and useful.\nYou day-to-day will often change, but it may include:\nGet to know our customer’s data: Work directly with customers and data partners to gain a deep understanding of their data contents and structures. Act as a liaison between technical teams and data providers, translating business needs into technical requirements.\nManage data integrations: Write detailed specifications for integrating new data sources into our existing tech stack. Develop robust and efficient code to implement these integrations, ensuring smooth data flow and compatibility.\nBuild smart data models: You'll use our frameworks to create queries that find valuable facts in different types of data. These data models will be the foundation for smart designs and speedy processing.\nWork across the technology stack: Use NoSQL datastores, like Apache Cassandra and Google Bigtable. Leverage data analytic tools such as Apache Spark and Apache Kafka to process and analyze large datasets.\nQualifications\nNote: These are guidelines, not hard requirements! If you think you’d be a good fit, please apply.\nDegree in Statistics, Data Science, Computer Science, Mathematics,, Engineering, or a related quantitative field.\n3-5+ years work experience on data engineering or similar\nExperience working directly with customers or stakeholders to gather data requirements\nProficiency in at least one programming language commonly used in data engineering (e.g., C++, Python, Java, Scala)\nStrong experience with NoSQL databases\nHands-on experience with big data processing tools, especially Apache Spark and Apache Kafka\nSolid understanding of data modeling principles and best practices\nFamiliarity with cloud platforms (e.g., AWS, Google Cloud, Azure) and their data services\nCompensation and Benefits\nSan Francisco Bay Area/Hybrid preferred, remote considered.\n$120k-150k with equity in an early-stage startup\nCompetitive benefits\n20 days PTO + paid holidays + unlimited sick leave\n401K\nHealthcare\nCompensation Range: $120K - $150K","datePosted":"2026-04-12T20:37:22.057Z","dateModified":"2026-04-12T20:37:22.057Z","hiringOrganization":{"@type":"Organization","name":"Infactory","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"15cf7dbfb9fe12b65eec9529"},"url":"https://jobsearcher.com/jobs/15cf7dbfb9fe12b65eec9529"}}