Principal Engineer, AutoQC and Data Consumption Solutions

Role Summary

We are seeking a data-driven, scientifically literate, and technically skilled Principal Engineer to serve as the Automated Data QC and Reporting Solutions lead. This role will automate and streamline pre-clinical data pipelines and reporting processes, ensuring the accuracy, consistency, and integrity of high-impact, regulatory documents across research laboratories. You will drive modernization and standardization of data pipelines and reporting, and develop strategies for data consumption solutions and reporting using AI capabilities to scale data environments.

Responsibilities

• Develop and execute modernization and standardization initiatives for automated QC and reporting of research data, ensuring alignment with business objectives and digital transformation goals.
• Lead development of data consumption solution strategies and reporting frameworks to enable scalable, future-ready, 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.
• Identify and prepare raw data files in response to regulatory requests.
• Deliver automated solutions that digitize and prepare raw data files in response to regulatory requests.
• Ensure the accuracy, completeness, traceability, and consistency of data across research business-critical documents.
• Ensure generated reports meet formatting, regulatory, data integrity, and quality standards.
• Identify and resolve data discrepancies using automated processes, collaborating with stakeholders.
• Collaborate across the Data Technology & Engineering organization and with research scientists to ensure solutions integrate with the 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.

Qualifications

• Required: Experience designing and implementing data and technology solutions in life sciences research and development.
• Required: Advanced programming skills in R and Python, and experience with database access, querying, and large dataset interrogation.
• Required: Expertise in agentic workflows, AI/ML technologies, and cloud-native platforms for data engineering and reporting.
• Required: Proficiency in evaluating and implementing new tools and technologies, including AI and agentic workflows.
• Required: Proficiency in data management and automation principles and methodologies.
• Required: Knowledge of statistics, data visualization, and scientific reporting.
• Required: Familiarity with data quality, reporting, and compliance requirements in regulated environments.
• Required: Excellent collaboration, interpersonal, and communication skills, with the ability to present complex technical concepts to diverse audiences.
• Required: Strong analytical, problem-solving, and decision-making skills using data-driven approaches.
• Required: Strong collaboration and inter-personal skills.
• Required: Proven track record of working in a complex, fast-paced environment.
• Required: Willingness to travel up to 10%.

Education

• Required: Bachelor's degree in Computer Science, Data Science, Engineering, or a related discipline or equivalent experience; advanced degree preferred.
• Required: 5+ years of experience in technical leadership, data management, or related roles within the biotechnology or pharmaceutical industry.
• Required: Proven track record of leveraging data engineering, software engineering and/or data science skills to automate reporting.
• Required: Proficiency in digital platforms and technologies, with the ability to evaluate and implement new tools and technologies.
• Required: Proven track record in leading digital transformation, modernization, and standardization initiatives.