{"schemaVersion":"jobsearcher.job.v1","id":"d51b86cc6c0425f66d0f2b94","url":"https://jobsearcher.com/jobs/d51b86cc6c0425f66d0f2b94","canonicalUrl":"https://jobsearcher.com/jobs/d51b86cc6c0425f66d0f2b94","title":"Data engineer with Supply Chain","description":"Own data quality alerting and issue management in Databricks: alert coverage, triage, routing, SLAs, root-cause analysis and closure; keep DQ and abnormality checks current as pipelines change; report DQ health to stakeholders.\r\nOwn metric definitions, calculations and measurement standards across functions; set certification standards and the governance gate metrics must pass before official reporting; mentor analysts, data engineers and BI developers.\r\nWork with analytics engineers to architect and govern the Databricks Gold layer: certified data models with embedded DQ and abnormality checks, metric views and data lineage.\r\nDrive data readiness for AI: tiered assessments scoring datasets on completeness, accuracy and automation readiness, and turn certified metrics into natural-language queryable experiences.\r\nMust-have skills\r\nDatabricks hands-on, including curated or Gold-layer data models [Databricks, Delta Lake, lakehouse, medallion, Gold layer].\r\nData quality ownership: DQ checks, anomaly or abnormality detection, alerting, SLAs, root-cause analysis [data quality, DQ, data observability, anomaly detection].\r\nMetric governance: metric definitions and certification, semantic layer or metric views, data lineage, data governance [metric definitions, semantic layer, metric views, data lineage, data catalog].\r\nSolutioning and transformation: has architected or led a data platform build, migration or modernization, not only operated pipelines [architect, solution design, transformation, migration, modernization].\r\nNice-to-haves: supply chain or hardware operations data; AI readiness or natural-language query on metrics (text-to-SQL, AI/BI); mentoring or leading engineers; senior level by years and scope; profile signals open to work.#J-18808-Ljbffr","company":"Sharpedge Solutions","rawCompany":"sharpedge solutions","city":"Millbrae","state":"CA","isRemote":false,"isActive":true,"createdAt":"2026-11-13T01:37:10.895Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data engineer with Supply Chain","description":"Own data quality alerting and issue management in Databricks: alert coverage, triage, routing, SLAs, root-cause analysis and closure; keep DQ and abnormality checks current as pipelines change; report DQ health to stakeholders.\r\nOwn metric definitions, calculations and measurement standards across functions; set certification standards and the governance gate metrics must pass before official reporting; mentor analysts, data engineers and BI developers.\r\nWork with analytics engineers to architect and govern the Databricks Gold layer: certified data models with embedded DQ and abnormality checks, metric views and data lineage.\r\nDrive data readiness for AI: tiered assessments scoring datasets on completeness, accuracy and automation readiness, and turn certified metrics into natural-language queryable experiences.\r\nMust-have skills\r\nDatabricks hands-on, including curated or Gold-layer data models [Databricks, Delta Lake, lakehouse, medallion, Gold layer].\r\nData quality ownership: DQ checks, anomaly or abnormality detection, alerting, SLAs, root-cause analysis [data quality, DQ, data observability, anomaly detection].\r\nMetric governance: metric definitions and certification, semantic layer or metric views, data lineage, data governance [metric definitions, semantic layer, metric views, data lineage, data catalog].\r\nSolutioning and transformation: has architected or led a data platform build, migration or modernization, not only operated pipelines [architect, solution design, transformation, migration, modernization].\r\nNice-to-haves: supply chain or hardware operations data; AI readiness or natural-language query on metrics (text-to-SQL, AI/BI); mentoring or leading engineers; senior level by years and scope; profile signals open to work.#J-18808-Ljbffr","datePosted":"2026-11-13T01:37:10.895Z","dateModified":"2026-11-13T01:37:10.895Z","hiringOrganization":{"@type":"Organization","name":"Sharpedge Solutions","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"d51b86cc6c0425f66d0f2b94"},"url":"https://jobsearcher.com/jobs/d51b86cc6c0425f66d0f2b94"}}