Principal Engineer, AutoQC and Data Consumption Solutions

Vertex Inc.•San Diego, CA

2d•Hybrid

About The Position

Vertex is a global biotechnology company that invests in scientific innovation. The Data, Technology and Engineering (DTE) Research, Pre-Clinical, Manufacturing & Supply (RPMS) Group’s mission is to improve the lives of patients through digital, data, and technology innovation. Vertex is in a transformational period where we are accelerating our capabilities, technology and data to augment our scientific mission and enable Vertex to grow in scale; ensuring we remain on the forefront of science, medicine and technology. Role Overview 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.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. This role will drive the modernization and standardization of data pipelines and reporting processes, ensuring accuracy, consistency, and integrity of high-impact, business-critical regulatory documents across research laboratories. The Principal Engineer will also develop and execute strategies for data consumption solutions and reporting, leveraging advanced technology, agentic workflows, and AI capabilities to modernize and scale data consumption environments.

Requirements

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 collaboration and inter-personal skills.
Proven track record of working in a complex, fast-paced environment.
Willingness to travel as needed (up to 10%) to support business objectives.
Bachelor's degree in a relevant field such as Computer Science, Data Science, Engineering, or a related discipline or equivalent experience; advanced degree preferred.
5+ years of experience in technical leadership, data management, or related roles within the biotechnology or pharmaceutical industry.
Proven track record of leveraging data engineering, software engineering and or data science skills to automate reporting.
Proficiency in digital platforms and technologies, with the ability to evaluate and implement new tools and technologies.
Proven track record in leading digital transformation, modernization, and standardization initiatives.

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 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.
Deliver solutions to automate and digitalize by identifying and preparing raw data files in response to regulatory requests.
Design, configure, develop and maintain automated solutions, tools and workflows for automated QC and report generation.
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.