Manager, Platform Data Architecture

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

At Thermo Fisher’s PPD clinical research business (CRG), we’re using digital innovation, data science, and AI to reimagine how life-changing therapies reach patients. Our teams combine deep scientific expertise with advanced analytics, automation, and digital platforms to make research smarter, faster, and more connected.

We know that innovation happens when diverse minds meet. Our Digital Science, Data, and AI professionals collaborate closely with scientists, clinicians, and operational experts to solve real-world challenges in clinical research. Alongside our partnership with Open AI, you can be part of the collaboration that will help to improve the speed and success of drug development, enabling customers to get medicines to patients faster and more cost effectively.

You’ll join a culture that values experimentation, learning, and collaboration — where your ideas can help shape how we deliver life-saving solutions and improve global health outcomes. 

Manager, Platform Data Architecture

The Manager, Platform Data Architecture serves as a central point of accountability for data architecture, data modeling and cross-platform alignment for Clinical Analytics Data Modeling, including ensuring data integrity, traceability, and audit readiness.

This is a hands-on role that leads a small team of developers, ensuring alignment with business objectives and enterprise data strategy. The ideal candidate brings deep technical expertise in modern data ecosystems along with strong leadership and cross-functional collaboration skills.

This is a home-based position for candidates on the East Coast US, EST time zone.

Key Responsibilities

• Manage and mentor a team of data developers, fostering technical excellence and professional growth 
• Define and enforce data architecture standards, best practices, and governance frameworks 
• Partner with business stakeholders, IT leadership, and product teams to translate business requirements into scalable data solutions 
• Oversee data integration strategies across internal and external systems (ETL/ELT, APIs, streaming) 
• Ensure data quality, security, privacy, and compliance with regulatory standards (e.g., GDPR, HIPAA as applicable) 
• Support analytics, AI/ML, and reporting initiatives by enabling accessible and well-structured data assets 
• Develop and maintain data engineering architecture documentation, including design specifications, data flow diagrams, and interface guidelines.
• Monitor and troubleshoot data engineering processes, identifying and resolving issues to ensure reliable and efficient data flow.
• Drive continuous improvement in data engineering practices, adopting new technologies and methodologies to enhance the engineering process.
• Provide regular updates and reports to senior management on data engineering projects, status, risks, and opportunities.
• Foster a collaborative and innovative team culture, encouraging professional growth and development.

Education and Experience:

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field (Advanced degree preferred)
• Previous data architecture or data engineering experience that provides the knowledge, skills, and abilities to perform the job (comparable to 8+ years’ experience).
• 2+ years of experience managing technical teams 
• In some cases an equivalency, consisting of appropriate education, training, and/or directly related experience will be considered sufficient for an individual to meet the requirements of the role.

Knowledge, Skills and Abilities:

• 5+ years of hands-on experience with DBT/Python, Talend and Snowflake/Databricks in production environment
• Solid SQL and understanding of database technologies like Snowflake, Databricks 
• Excellent problem-solving skills and the ability to think strategically.
• Strong experience with cloud platforms (AWS, Azure, or GCP) and modern data stack technologies 
• Expertise in data modeling, database design (SQL/NoSQL), and data integration frameworks 
• Experience with big data technologies (e.g., Spark, Hadoop, Kafka) 
• Solid understanding of data governance, data quality, and security best practices 
• Experience in regulated industries (e.g., healthcare, life sciences, finance) (preferred)
• Familiarity with data mesh or data fabric architectures (preferred)
• Certifications in cloud platforms or data architecture (preferred)
• Demonstrated leadership abilities with a focus on team development
• Proven track record in process improvement and