Staff Data Platform Architect

Work Schedule

Environmental Conditions

Job Description

As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.
Description

We are looking for an experienced Data Platform Architect to design, build, and optimize scalable data platforms that power AI, analytics, and automation initiatives. This role will be responsible for architecting robust cloud-based data ecosystems, ensuring performance, cost efficiency, and reliability across enterprise data platforms.

Experience Required

• 10+ years of overall professional experience
• 5+ years of experience as a Data Platform Architect (AWS, DataBricks, DevOps) or similar role

Key Responsibilities

• Define and implement the architecture for scalable data platforms supporting analytics, AI, and automation use cases
• Design and optimize data pipelines, data lakes, and data warehouses on cloud platforms
• Lead platform engineering efforts on AWS, DataBricks, DevOps environments
• Ensure high availability, scalability, performance, and security of data platforms
• Drive cloud cost optimization strategies and monitor usage efficiency
• Continuously improve system performance, reliability, and throughput
• Collaborate with cloud vendors to adopt new features and best practices
• Establish and maintain version control, data backup, and disaster recovery strategies
• Enable seamless integration of data engineering, AI/ML, and automation workflows
• Support governance, compliance, and data quality frameworks

Required Skills & Qualifications

• Strong expertise in AWS cloud services related to data engineering, AI, and automation
• Hands-on experience with Databricks platform (development and support)
• Strong experience in designing scalable data processing and pipeline architectures
• Proven experience in cloud cost optimization and performance tuning
• Experience in managing scalable computing environments in cloud
• Hands-on experience with:
  • SQL
  • Python
  • R
• Experience with version control systems (e.g., Git) and data backup strategies
• Strong understanding of distributed computing and big data technologies
• Excellent problem-solving and analytical skills

Data Visualization & Monitoring

• Hands-on experience with Power BI and/or Tableau
• Ability to build dashboards for monitoring platform performance and application quality metrics

Preferred Qualifications

• Experience with DevOps practices and tools (GitHub, GitHub Actions)
• Experience supporting and optimizing Databricks platforms at scale
• Exposure to AI/ML initiatives and integration with data platforms
• Exposure to Microsoft Power BI capacity platform support.
• Relevant cloud or data platform certifications (AWS, Databricks, etc.)
• Familiarity with data governance frameworks, security best practices, and regulatory compliance (e.g., GxP, GDPR, HIPAA).
• Internal integration/external integration with data. Standardize integration process.

Key Competencies

• Strong architectural thinking and system design skills
• Performance optimization and cost efficiency mindset
• Ability to manage complex, large-scale data platforms
• Strong collaboration with cross-functional teams
• Continuous learning and adoption of new technologies

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field

Why Join Us

• Opportunity to architect next-generation data platforms
• Work on cutting-edge data, AI, and automation initiatives
• Collaborative and innovation-driven environment
• Strong career growth opportunities