Principal Engineer, Automated Data QC and Reporting Solutions

Job Description

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. 

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.

The Principal Engineer, Automated Data QC and Reporting solutions will be responsible for delivering data and technology solutions that digitalize and automate with precision and urgency:

• Identification and preparation of raw data files requested by regulatory agencies and support regulatory inspection readiness

• Generation of scientific study reports for post-file activities such as label expansion

• Assurance of quality control (QC) of critical data within data packages and documents used in Vertex research study reports

You will work closely with cross-functional teams to streamline workflows associated with report generation, improve data accuracy, and ensure compliance with regulatory standards.

Key Duties and Responsibilities 

Vision and Strategy

• Develop and execute the data and technology initiatives for automated QC and reporting of research data, ensuring alignment with business objectives to deliver a digital transformation with q the velocity of highly impactful data packages and reports.

• Identify and implement innovative digital technologies to improve capabilities, ensuring scalability and future readiness.

• Collaborate with cross-functional teams to align global digital QC and reporting strategies across multiple research sites.

Operational Execution

• 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.

• Regularly evaluate and optimize solutions, scripts, and workflows to enhance performance and scalability.

• 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.

Collaboration and Communication

• 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. 

Required Knowledge and Skills 

• Understanding and experience of designing and implementing data and technology solutions in life sciences research and development.

• Proficiency in data management and automation principles and methodologies.

• Expertise in at least one or more programming languages including R and Python.

• Expertise in interrogating large datasets via database access and query.

• Knowledge of statistics.

• Strong analytical and problem-solving skills, with the ability to use data to inform decisions.

• Strong collaborati