Principal Engineer, AutoQC and Data Consumption Solutions

Principal Engineer, AutoQC and Data Consumption Solutions

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We are seeking a data driven, scientifically literate, and technically skilled Principal Engineer to serve as the Automated Data QC and Reporting Solutions lead to automate and streamline pre-clinical data pipelines and reporting processes and ensure the accuracy, consistency, and integrity of high impact, high visibility, and business-critical regulatory documents across research laboratories.

• Develop and execute modernization and standardization initiatives for automated QC and reporting of research data, ensuring alignment with business objectives and digital transformation.
• Lead the development of data consumption solution strategies and reporting frameworks to enable scalable, future‑ready, and unified data environments.
• Identify and implement innovative digital and AI‑powered technologies, including agentic workflows, to enhance data consumption, reporting, and scientific insight generation.
• Collaborate with cross‑functional teams to align global digital QC, reporting, and data consumption strategies across multiple research sites.

• Design, configure, develop, and maintain automated solutions, tools, and workflows for QC, report generation, and standardized data consumption.
• Regularly evaluate and optimize solutions, scripts, and workflows to enhance performance, scalability, and interoperability.
• Identify and prepare raw data files in response to regulatory requests.
• Ensure the accuracy, completeness, traceability and consistency of data across research business‑critical documents (e.g. research study reports).
• Ensure generated reports meet formatting, regulatory, data integrity, and quality standards.
• Identify and resolve data discrepancies using automated processes, collaborating with stakeholders.
• Collaborate across our Data Technology & Engineering (DTE) organization and with research scientists to ensure solutions integrate with our broader data platform and data engineering strategy.
• Ensure the accuracy, security, quality and business continuity of solutions in line with Vertex and external data and technology standards.

• Drive the adoption of agentic workflows and AI capabilities to automate and accelerate scientific data workflows, reporting, and consumption interfaces.
• Develop and deploy AI‑enhanced visualization, reporting, and QC interpretation tools.
• Champion the use of cloud‑native and unified semantic consumption layers for scalable data access and analysis.

• Partner with scientists, statisticians, and program representatives to understand reporting and QC requirements.
• Partner with DTE leaders to understand and deliver to data and technical requirements.
• Provide leadership and training to a team of super users on automated QC and report generation workflows to ensure business continuity.
• Develop a sustainable suite of solutions that minimize future training.
• Deliver solutions and insights with clear and actionable QC and reporting summaries to stakeholders.

• Experience designing and implementing data and technology solutions in life sciences research and development.
• Advanced programming skills in R, Python, and experience with database access, query, and large dataset interrogation.
• Expertise in agentic workflows, AI/ML technologies, and cloud‑native platforms for data engineering and reporting.
• Proficiency in evaluating and implementing new tools and technologies, including AI and agentic workflows.
• Proficiency in data management and automation principles and methodologies.
• Knowledge of statistics, data visualization, and scientific reporting.
• Familiarity with data quality, reporting, and compliance requirements in regulated environments.
• Excellent collaboration, interpersonal, and communication skills, with the ability to present complex technical concepts to diverse audiences.
• Strong analytical, problem‑solving, and decision‑making skills using data‑driven approaches.
• Strong…