{"schemaVersion":"jobsearcher.job.v1","id":"4188ed8acb86dc92f2f9e17c","url":"https://jobsearcher.com/jobs/4188ed8acb86dc92f2f9e17c","canonicalUrl":"https://jobsearcher.com/jobs/4188ed8acb86dc92f2f9e17c","title":"Protocol Data Engineer","description":"POSITION TITLE: Protocol Data Engineer\n\nLOCATION: Remote\n\nCLEARANCE: Must be able to obtain a High-Risk Public Trust\n\nCOMPANY OVERVIEW\n\nAt APV, we’re more than a technology company — we’re a mission-driven powerhouse transforming organizations through advanced technology and human ingenuity. Our expertise spans AI/ML, data architecture, low-code/no-code development, Agile DevSecOps, and cloud services, delivering scalable and meaningful solutions.\n\nIn our Emerging Technology Lab, innovation drives progress. Our teams create intelligent chatbots, AI-powered assistants, robotic process automation (RPA), essay graders, and data analytics platforms. If you’re passionate about solving complex challenges and shaping the future, APV is the place for you. Since 2007, we’ve partnered with federal and state agencies to deliver IT, training, and consulting solutions that achieve mission-critical outcomes. Built on accountability, integrity, and quality, we go beyond expectations. With 70+ prime contracts and a proven record of client success, APV continues to grow — and we’re looking for exceptional talent to grow with us.\n\nAt APV, we Always Provide Value\n\nPOSITION SUMMARY\n\nProvides hands-on data engineering and database implementation expertise to operationalize structured protocol data models and support the FDA proof of concept for AI-assisted clinical trial protocol review. The role translates approved clinical, standards, and technical models into scalable data structures, transformations, retrieval workflows, and traceable outputs within FDA-approved environments.\n\nDUTIES\n\nImplement protocol data structures and physical schemas that support extraction, normalization, storage, retrieval, comparison, and reviewer-facing use of both ICH M11-aligned and historical protocols.\nTranslate approved ICH M11, CDISC USDM, ontology, metadata, and terminology models into practical database structures and data-engineering components for the POC.\nDevelop and support ETL/ELT pipelines and data transformations for protocol content and structured outputs, preserving source provenance, metadata, assumptions, validation status, and reviewer feedback.\nSupport retrieval-augmented generation (RAG), semantic retrieval, indexing, evidence caching, and protocol comparison components in collaboration with AI/prompt engineering and standards SMEs.\nSupport integration with FDA-furnished Elsa/HALO capabilities and FDA-approved data services, including PostgreSQL and/or HALO/Databricks, for protocol evidence caching, retrieval, analytics, and dashboard-ready outputs.\nDevelop advanced SQL and data-access logic supporting protocol extraction, historical retrieval and comparison, reviewer dashboards, and traceability to source evidence.\nExecute data-focused quality assurance, reconciliation, validation, and regression testing, including checks for completeness, mapping consistency, retrieval quality, unsupported values, ambiguity, and reproducibility.\nDocument data models, interfaces, transformations, mappings, implementation decisions, technical limitations, and operational considerations to support FDA review, knowledge transfer, and future expansion.\nWorks closely with clinical protocol, data standards, architecture, interoperability, and AI/prompt engineering SMEs.\nParticipates in FDA technical working sessions, POC demonstrations, validation activities, and iterative refinement based on reviewer feedback.\nSupports implementation within FDA-provided platforms and approved data environments; the base effort is a POC and does not require a separate production platform.\nContributes practical database engineering and data-quality expertise while relying on designated SMEs for clinical interpretation and standards governance.\n\nEDUCATION\n\nBS degree in Computer Science, Mathematics, Data Science or relevant technical field.\n\nREQUIRED QUALIFICATIONS\n\nExtensive experience in database engineering, data architecture, information modeling, and analytics in complex enterprise environments.\nStrong expertise in relational and dimensional data modeling, metadata management, ETL/ELT design, data warehousing, and data quality.\nAdvanced SQL skills, including PostgreSQL/PLpgSQL and/or Oracle PL/SQL; SQL Server experience is beneficial.\nExperience with AWS data services and cloud database platforms such as Aurora PostgreSQL, Redshift, S3, Glue, Lambda, and DMS.\nExperience integrating JSON/XML data and RESTful APIs; working knowledge of Python and CI/CD practices is beneficial.\nFederal health, clinical research, or regulated-environment experience is preferred; familiarity with FISMA/NIST controls is beneficial.\n\nABOUT APV\n\nAPV is an Equal Employment Opportunity employer. All qualified applicants are considered without regard to race, color, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity, veteran status, or marital status.","company":"Apventuresll","rawCompany":"apventuresll","city":"Myrtle Point","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-10-02T13:27:11.212Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-2051.02","title":"Clinical Data Managers","slug":"clinical-data-managers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Protocol Data Engineer","description":"POSITION TITLE: Protocol Data Engineer\n\nLOCATION: Remote\n\nCLEARANCE: Must be able to obtain a High-Risk Public Trust\n\nCOMPANY OVERVIEW\n\nAt APV, we’re more than a technology company — we’re a mission-driven powerhouse transforming organizations through advanced technology and human ingenuity. Our expertise spans AI/ML, data architecture, low-code/no-code development, Agile DevSecOps, and cloud services, delivering scalable and meaningful solutions.\n\nIn our Emerging Technology Lab, innovation drives progress. Our teams create intelligent chatbots, AI-powered assistants, robotic process automation (RPA), essay graders, and data analytics platforms. If you’re passionate about solving complex challenges and shaping the future, APV is the place for you. Since 2007, we’ve partnered with federal and state agencies to deliver IT, training, and consulting solutions that achieve mission-critical outcomes. Built on accountability, integrity, and quality, we go beyond expectations. With 70+ prime contracts and a proven record of client success, APV continues to grow — and we’re looking for exceptional talent to grow with us.\n\nAt APV, we Always Provide Value\n\nPOSITION SUMMARY\n\nProvides hands-on data engineering and database implementation expertise to operationalize structured protocol data models and support the FDA proof of concept for AI-assisted clinical trial protocol review. The role translates approved clinical, standards, and technical models into scalable data structures, transformations, retrieval workflows, and traceable outputs within FDA-approved environments.\n\nDUTIES\n\nImplement protocol data structures and physical schemas that support extraction, normalization, storage, retrieval, comparison, and reviewer-facing use of both ICH M11-aligned and historical protocols.\nTranslate approved ICH M11, CDISC USDM, ontology, metadata, and terminology models into practical database structures and data-engineering components for the POC.\nDevelop and support ETL/ELT pipelines and data transformations for protocol content and structured outputs, preserving source provenance, metadata, assumptions, validation status, and reviewer feedback.\nSupport retrieval-augmented generation (RAG), semantic retrieval, indexing, evidence caching, and protocol comparison components in collaboration with AI/prompt engineering and standards SMEs.\nSupport integration with FDA-furnished Elsa/HALO capabilities and FDA-approved data services, including PostgreSQL and/or HALO/Databricks, for protocol evidence caching, retrieval, analytics, and dashboard-ready outputs.\nDevelop advanced SQL and data-access logic supporting protocol extraction, historical retrieval and comparison, reviewer dashboards, and traceability to source evidence.\nExecute data-focused quality assurance, reconciliation, validation, and regression testing, including checks for completeness, mapping consistency, retrieval quality, unsupported values, ambiguity, and reproducibility.\nDocument data models, interfaces, transformations, mappings, implementation decisions, technical limitations, and operational considerations to support FDA review, knowledge transfer, and future expansion.\nWorks closely with clinical protocol, data standards, architecture, interoperability, and AI/prompt engineering SMEs.\nParticipates in FDA technical working sessions, POC demonstrations, validation activities, and iterative refinement based on reviewer feedback.\nSupports implementation within FDA-provided platforms and approved data environments; the base effort is a POC and does not require a separate production platform.\nContributes practical database engineering and data-quality expertise while relying on designated SMEs for clinical interpretation and standards governance.\n\nEDUCATION\n\nBS degree in Computer Science, Mathematics, Data Science or relevant technical field.\n\nREQUIRED QUALIFICATIONS\n\nExtensive experience in database engineering, data architecture, information modeling, and analytics in complex enterprise environments.\nStrong expertise in relational and dimensional data modeling, metadata management, ETL/ELT design, data warehousing, and data quality.\nAdvanced SQL skills, including PostgreSQL/PLpgSQL and/or Oracle PL/SQL; SQL Server experience is beneficial.\nExperience with AWS data services and cloud database platforms such as Aurora PostgreSQL, Redshift, S3, Glue, Lambda, and DMS.\nExperience integrating JSON/XML data and RESTful APIs; working knowledge of Python and CI/CD practices is beneficial.\nFederal health, clinical research, or regulated-environment experience is preferred; familiarity with FISMA/NIST controls is beneficial.\n\nABOUT APV\n\nAPV is an Equal Employment Opportunity employer. All qualified applicants are considered without regard to race, color, religion, sex, national origin, age, disability, genetic information, sexual orientation, gender identity, veteran status, or marital status.","datePosted":"2026-10-02T13:27:11.212Z","dateModified":"2026-10-02T13:27:11.212Z","hiringOrganization":{"@type":"Organization","name":"Apventuresll","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Myrtle Point","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"4188ed8acb86dc92f2f9e17c"},"url":"https://jobsearcher.com/jobs/4188ed8acb86dc92f2f9e17c"}}