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Protocol Data Engineer

A P Ventures LLC Remote 🌍 Remote

Remote

Today

Full time Amazon Web Services Artificial Intelligence AWS

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Job Description

A P Ventures LLC is seeking a Protocol Data Engineer to support an FDA proof of concept for AI-assisted clinical trial protocol review. This remote role focuses on turning approved protocol, standards, and terminology models into reliable, scalable database structures, transformations, and retrieval workflows inside FDA-approved environments.

You will work hands-on with protocol data structures and evidence traceability, collaborating with clinical protocol, data standards, architecture, interoperability, and AI/prompt engineering SMEs throughout development, validation, and iterative refinement based on reviewer feedback.

Responsibilities

Implement protocol data structures and physical schemas to enable extraction, normalization, storage, retrieval, comparison, and reviewer-facing use across both ICH M11-aligned and historical protocols.
Translate approved ICH M11, CDISC USDM, ontology, metadata, and terminology models into practical database structures and POC data-engineering components.
Develop and support ETL/ELT pipelines and data transformations for protocol content and structured outputs, preserving source provenance, metadata, assumptions, validation status, and reviewer feedback.
Collaborate with AI/prompt engineering and standards SMEs on RAG, semantic retrieval, indexing, evidence caching, and protocol comparison components.
Support integration with FDA-furnished Elsa/HALO capabilities and FDA-approved data services, including PostgreSQL and/or HALO/Databricks, for evidence caching, retrieval, analytics, and dashboard-ready outputs.
Build advanced SQL and data-access logic for protocol extraction, historical retrieval and comparison, reviewer dashboards, and traceability to source evidence.
Perform data-focused quality assurance, reconciliation, validation, and regression testing, including checks for completeness, mapping consistency, retrieval quality, unsupported values, ambiguity, and reproducibility.
Document data models, interfaces, transformations, mappings, implementation decisions, technical limitations, and operational considerations to support FDA review, knowledge transfer, and future expansion.
Work closely with clinical protocol, data standards, architecture, interoperability, and AI/prompt engineering SMEs.
Participate in FDA technical working sessions, POC demonstrations, validation activities, and iterative refinement driven by reviewer feedback.
Support implementation within FDA-provided platforms and approved data environments, with the base effort limited to a POC that does not require a separate production platform.
Contribute database engineering and data-quality expertise while relying on designated SMEs for clinical interpretation and standards governance.

Requirements

Extensive experience in database engineering, data architecture, information modeling, and analytics in complex enterprise environments.
Strong expertise in relational and dimensional data modeling, metadata management, ETL/ELT design, data warehousing, and data quality.
Advanced SQL skills, including PostgreSQL/PLpgSQL and/or Oracle PL/SQL; SQL Server experience is beneficial.
Experience with AWS data services and cloud database platforms such as Aurora PostgreSQL, Redshift, S3, Glue, Lambda, and DMS.
Experience integrating JSON/XML data and RESTful APIs; working knowledge of Python and CI/CD practices is beneficial.
Federal health, clinical research, or regulated-environment experience is preferred; familiarity with FISMA/NIST controls is beneficial.

Technologies

PostgreSQL, PLpgSQL, Oracle PL/SQL, SQL Server
AWS, Aurora PostgreSQL, Redshift, S3, Glue, Lambda, DMS
JSON, XML, RESTful APIs, Python, CI/CD
Elsa/HALO, HALO/Databricks
ETL/ELT, RAG
FISMA, NIST
ICH M11, CDISC USDM

Location

Remote

Clearance

Must be able to obtain a High-Risk Public Trust

Education

BS degree in Computer Science, Mathematics, Data Science or relevant technical field

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