{"schemaVersion":"jobsearcher.job.v1","id":"79b7f0bff8461b63c629bc44","url":"https://jobsearcher.com/jobs/79b7f0bff8461b63c629bc44","canonicalUrl":"https://jobsearcher.com/jobs/79b7f0bff8461b63c629bc44","title":"Senior Staff Data Engineer","description":"About Us Circle (NYSE: CRCL) is one of the world's leading internet financial platform companies, building the foundation of a more open, global economy through digital assets, payment applications, and programmable blockchain infrastructure. Circle's platform includes the world's largest regulated stablecoin network anchored by USDC, Circle Payments Network for global money movement, and Arc, an enterprise-grade blockchain designed to become the Economic OS for the internet. Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale financial innovation.\r\nCircle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values: High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. We have built a flexible work environment where new ideas are encouraged and everyone is a stakeholder.\r\nThe Role You will define and drive the strategy for data reliability, quality, and operational excellence across the organization, shaping how Circle builds and trusts its data ecosystem. This includes establishing company-wide standards for data quality, contracts, and governance; designing scalable reliability and observability frameworks; and institutionalizing incident management practices that promote a culture of accountability and continuous improvement. You will influence platform and architectural decisions to ensure long-term scalability, reduce systemic risk, and eliminate classes of failure across the data landscape. As a senior technical leader, you will also guide cross-team prioritization of reliability investments, define best-in-class data engineering practices, and lead complex, high-impact initiatives in ambiguous environments—driving alignment, mitigating risk, and delivering robust, scalable data solutions.\r\nResponsibilities Define and implement organization-wide data quality standards, including data contracts, SLAs, and governance frameworks across domains\r\nDesign and scale reliability and observability frameworks, including SLI/SLO models, lineage tracking, monitoring, and alerting patterns\r\nEstablish and evolve incident management practices, including severity models, escalation paths, on-call structures, and blameless postmortems\r\nDevelop and standardize data engineering SDLC practices, including testing strategies, CI/CD, versioning, and reusable frameworks\r\nDrive cross-functional prioritization of reliability initiatives, balancing technical debt, operational health, and product delivery across teams\r\nLead ecosystem-wide platform improvements, identifying architectural gaps, reducing fragmentation, and influencing build vs buy decisions\r\nOwn and deliver complex, high-impact data initiatives, aligning stakeholders, mitigating risks, and driving scalable solutions in ambiguous environments\r\nRequirements Extensive experience designing and operating scalable data platforms with a focus on reliability, quality, and observability\r\nExperience leveraging AI tools and methodologies to design and implement solutions\r\nDeep expertise in data architecture, including data modeling, pipeline design, and distributed data systems\r\nProven ability to define and implement data quality frameworks, including SLAs, data contracts, and governance standards\r\nStrong experience establishing SLI/SLO frameworks, monitoring, and alerting for large-scale data systems\r\nDemonstrated ability to lead complex, cross-team technical initiatives and drive alignment across stakeholders\r\nExperience defining and scaling engineering best practices, including testing, CI/CD, and development standards for data systems\r\nNice to Have Experience building or evolving data platforms in high-growth or highly regulated environments (e.g., fintech, payments, crypto)\r\nFamiliarity with modern data tooling ecosystems, including orchestration, transformation, metadata, and observability platforms\r\nExperience with technologies such as Astronomer (Airflow), BigQuery, dbt, Dataplex, Kubernetes, and programming languages like Python or Go, or comparable tools in the modern data stack\r\nTrack record of influencing platform strategy, including build vs buy decisions and long-term architectural evolution\r\nCompensation Base Pay Range: $225,000 - $290,000\r\nCircle considers a wide variety of elements when crafting compensation ranges and total compensation packages. Starting pay is determined by various factors, including but not limited to: relevant experience, skill set, qualifications, and other business and organizational needs. Please note that compensation ranges may differ for candidates in other locations.\r\nJ-18808-Ljbffr","company":"Unchain Data","rawCompany":"unchain data","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-07T00:51:08.736Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"}],"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":"Senior Staff Data Engineer","description":"About Us Circle (NYSE: CRCL) is one of the world's leading internet financial platform companies, building the foundation of a more open, global economy through digital assets, payment applications, and programmable blockchain infrastructure. Circle's platform includes the world's largest regulated stablecoin network anchored by USDC, Circle Payments Network for global money movement, and Arc, an enterprise-grade blockchain designed to become the Economic OS for the internet. Enterprises, financial institutions, and developers use Circle to power trusted, internet-scale financial innovation.\r\nCircle is committed to visibility and stability in everything we do. As we grow as an organization, we're expanding into some of the world's strongest jurisdictions. Speed and efficiency are motivators for our success and our employees live by our company values: High Integrity, Future Forward, Multistakeholder, Mindful, and Driven by Excellence. We have built a flexible work environment where new ideas are encouraged and everyone is a stakeholder.\r\nThe Role You will define and drive the strategy for data reliability, quality, and operational excellence across the organization, shaping how Circle builds and trusts its data ecosystem. This includes establishing company-wide standards for data quality, contracts, and governance; designing scalable reliability and observability frameworks; and institutionalizing incident management practices that promote a culture of accountability and continuous improvement. You will influence platform and architectural decisions to ensure long-term scalability, reduce systemic risk, and eliminate classes of failure across the data landscape. As a senior technical leader, you will also guide cross-team prioritization of reliability investments, define best-in-class data engineering practices, and lead complex, high-impact initiatives in ambiguous environments—driving alignment, mitigating risk, and delivering robust, scalable data solutions.\r\nResponsibilities Define and implement organization-wide data quality standards, including data contracts, SLAs, and governance frameworks across domains\r\nDesign and scale reliability and observability frameworks, including SLI/SLO models, lineage tracking, monitoring, and alerting patterns\r\nEstablish and evolve incident management practices, including severity models, escalation paths, on-call structures, and blameless postmortems\r\nDevelop and standardize data engineering SDLC practices, including testing strategies, CI/CD, versioning, and reusable frameworks\r\nDrive cross-functional prioritization of reliability initiatives, balancing technical debt, operational health, and product delivery across teams\r\nLead ecosystem-wide platform improvements, identifying architectural gaps, reducing fragmentation, and influencing build vs buy decisions\r\nOwn and deliver complex, high-impact data initiatives, aligning stakeholders, mitigating risks, and driving scalable solutions in ambiguous environments\r\nRequirements Extensive experience designing and operating scalable data platforms with a focus on reliability, quality, and observability\r\nExperience leveraging AI tools and methodologies to design and implement solutions\r\nDeep expertise in data architecture, including data modeling, pipeline design, and distributed data systems\r\nProven ability to define and implement data quality frameworks, including SLAs, data contracts, and governance standards\r\nStrong experience establishing SLI/SLO frameworks, monitoring, and alerting for large-scale data systems\r\nDemonstrated ability to lead complex, cross-team technical initiatives and drive alignment across stakeholders\r\nExperience defining and scaling engineering best practices, including testing, CI/CD, and development standards for data systems\r\nNice to Have Experience building or evolving data platforms in high-growth or highly regulated environments (e.g., fintech, payments, crypto)\r\nFamiliarity with modern data tooling ecosystems, including orchestration, transformation, metadata, and observability platforms\r\nExperience with technologies such as Astronomer (Airflow), BigQuery, dbt, Dataplex, Kubernetes, and programming languages like Python or Go, or comparable tools in the modern data stack\r\nTrack record of influencing platform strategy, including build vs buy decisions and long-term architectural evolution\r\nCompensation Base Pay Range: $225,000 - $290,000\r\nCircle considers a wide variety of elements when crafting compensation ranges and total compensation packages. Starting pay is determined by various factors, including but not limited to: relevant experience, skill set, qualifications, and other business and organizational needs. Please note that compensation ranges may differ for candidates in other locations.\r\nJ-18808-Ljbffr","datePosted":"2026-08-07T00:51:08.736Z","dateModified":"2026-08-07T00:51:08.736Z","hiringOrganization":{"@type":"Organization","name":"Unchain Data","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"79b7f0bff8461b63c629bc44"},"url":"https://jobsearcher.com/jobs/79b7f0bff8461b63c629bc44"}}