{"schemaVersion":"jobsearcher.job.v1","id":"12930d0721bb655e2a226a6d","url":"https://jobsearcher.com/jobs/12930d0721bb655e2a226a6d","canonicalUrl":"https://jobsearcher.com/jobs/12930d0721bb655e2a226a6d","title":"Lead Data Engineer (Remote)","description":"Programming & Data Engineering Expert - level proficiency in Python, Scala, and PySpark, with a strong track record of designing and delivering production-ready, modular, and well-tested solutions; developing and troubleshooting Spark workloads; and optimizing large-scale batch and streaming data pipelines using Delta Lake and Spark technologies. Strong SQL and data modelling dimensional and normalised; schema design and data contract definition.Databricks expertise Delta Lake, Unity Catalog, Jobs & Workflows, cluster and pool management, performance tuning, Model Serving. Azure data stack — ADLS Gen2 (zone design, ACLs, lifecycle), Azure Data Factory (parameterized / metadata-driven frameworks, error handling), Azure Event Hubs. AI & Machine Learning ~3+ years designing and shipping LLM-based systems in production: RAG pipelines, agentic / tool-calling workflows, structured output, chunking and embedding strategy, vector and hybrid retrieval, and prompt engineering. ~ Evaluation discipline — golden datasets, regression suites, accuracy and hallucination tracking, human-in-the-loop feedback loops; you measure AI quality, not assert it. ~ Hands-on experience with LangChain, LlamaIndex, or LangGraph, plus at least one provider stack (Azure OpenAI, OpenAI, or Databricks Model Serving). ~ Metadata-driven thinking — schema inference, data profiling, lineage, catalogs, and configuration-driven frameworks that onboard the next source without new code.Architecture & Governance ~12–18 years of total experience in data engineering, data platform delivery, or related disciplines. ~ Proven delivery of a medallion/lakehouse architecture at enterprise scale — not just familiarity with the concept. ~ Azure security and governance: Entra ID, managed identities, RBAC, POSIX ACLs on ADLS Gen2, Key Vault, private endpoints, and PII handling. ~ CI/CD and infrastructure as code: Azure DevOps, Terraform, Databricks Asset Bundles, and automated testing of data pipelines. ~ Clear technical writing and the ability to present and defend a design to both engineers and non-technical stakeholders.","company":"Reuben Cooley","rawCompany":"reuben cooley","isRemote":true,"isActive":false,"createdAt":"2026-10-20T02:41:45.707Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Lead Data Engineer (Remote)","description":"Programming & Data Engineering Expert - level proficiency in Python, Scala, and PySpark, with a strong track record of designing and delivering production-ready, modular, and well-tested solutions; developing and troubleshooting Spark workloads; and optimizing large-scale batch and streaming data pipelines using Delta Lake and Spark technologies. Strong SQL and data modelling dimensional and normalised; schema design and data contract definition.Databricks expertise Delta Lake, Unity Catalog, Jobs & Workflows, cluster and pool management, performance tuning, Model Serving. Azure data stack — ADLS Gen2 (zone design, ACLs, lifecycle), Azure Data Factory (parameterized / metadata-driven frameworks, error handling), Azure Event Hubs. AI & Machine Learning ~3+ years designing and shipping LLM-based systems in production: RAG pipelines, agentic / tool-calling workflows, structured output, chunking and embedding strategy, vector and hybrid retrieval, and prompt engineering. ~ Evaluation discipline — golden datasets, regression suites, accuracy and hallucination tracking, human-in-the-loop feedback loops; you measure AI quality, not assert it. ~ Hands-on experience with LangChain, LlamaIndex, or LangGraph, plus at least one provider stack (Azure OpenAI, OpenAI, or Databricks Model Serving). ~ Metadata-driven thinking — schema inference, data profiling, lineage, catalogs, and configuration-driven frameworks that onboard the next source without new code.Architecture & Governance ~12–18 years of total experience in data engineering, data platform delivery, or related disciplines. ~ Proven delivery of a medallion/lakehouse architecture at enterprise scale — not just familiarity with the concept. ~ Azure security and governance: Entra ID, managed identities, RBAC, POSIX ACLs on ADLS Gen2, Key Vault, private endpoints, and PII handling. ~ CI/CD and infrastructure as code: Azure DevOps, Terraform, Databricks Asset Bundles, and automated testing of data pipelines. ~ Clear technical writing and the ability to present and defend a design to both engineers and non-technical stakeholders.","datePosted":"2026-10-20T02:41:45.707Z","dateModified":"2026-10-20T02:41:45.707Z","hiringOrganization":{"@type":"Organization","name":"Reuben Cooley","sameAs":"https://jobsearcher.com"},"jobLocationType":"TELECOMMUTE","applicantLocationRequirements":{"@type":"Country","name":"US"},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"12930d0721bb655e2a226a6d"},"url":"https://jobsearcher.com/jobs/12930d0721bb655e2a226a6d"}}