Sr Enterprise Data Architect

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πŸ“ United States
πŸ’° USD 125,000 - 175,000 / annual
πŸ“… Posted 2026-08-09 Β· via Himalayas
🏷 Enterprise-Data-Architect,Data-Architecture,Data-Engineering,Clinical-Research-Data,Enterprise-Architecture,Senior-Enterprise-Business-Architect,Senior-BI-Data-Architect,Principal-Data-Architect
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Job Title: Sr Enterprise Data Architect

Job Location: Remote, North Carolina, USA

Job Location Type: Remote

Job Contract Type: Full-time
Job Seniority Level:
Work Schedule
Standard (Mon-Fri) Environmental Conditions
Office Job Description

At Thermo Fisher Scientific's PPD Clinical Research Group (CRG), we're using digital innovation, data science, and AI to transform how life-changing therapies reach patients. Our Digital Science, Data, and AI teams combine scientific expertise with advanced analytics, automation, and digital platforms to make clinical research smarter, faster, and more connected.

Innovation happens when diverse minds come together. Our teams collaborate closely with scientists, clinicians, and operational experts to solve complex challenges in clinical research. Through our collaboration with OpenAI, we're helping accelerate drug development so customers can bring medicines to patients faster and more cost-effectively.

What You'll Do
Lead the enterprise data architecture strategy as a Senior Enterprise Data Architect (internally known as Sr Staff IT Architect, band 8) and help lead the design and implementation of enterprise-wide technology and data architecture across cloud infrastructure, cybersecurity, AI/ML, automation, and data platforms.

As a technical leader, you'll establish architectural standards, guide strategic technology initiatives, and partner with cross-functional teams to deliver scalable, secure, and innovative solutions that drive business growth and digital transformation.
Key Responsibilities

- Design enterprise-scale data and technology architecture solutions supporting clinical trials across global programs.

- Develop scalable, secure architectures spanning cloud infrastructure, AI/ML, automation, cybersecurity, and enterprise data platforms.

- Translate business requirements into robust architectural designs aligned with enterprise standards.

- Establish architecture best practices and provide technical leadership across strategic initiatives.

- Enable AI-driven clinical research by partnering with cross-functional teams and key stakeholders to deliver innovative solutions.

- Influence the enterprise technology roadmap and support digital transformation initiatives.

- Mentor and guide technical teams through complex architecture decisions.

Tech Stack:
Data & Analytics

- SQL, PL/SQL

- Databricks

- Snowflake

Data Architecture & Modeling

- Erwin Data Modeler (or equivalent)

- Data Modeling

- Data Mapping

- Metadata management

- Data Governance

- Data Lifecycle Management

- Enterprise Data Architecture

Cloud & Enterprise Technologies

- Cloud Infrastructure

- AI/ML (Artificial Intelligence & Machine Learning)

Education & Experience

- Bachelor's degree (or equivalent combination of education and experience) in relevant field; Masters’ degree preferred.

- 8+ years of experience in enterprise data or platform architecture, or equivalent experience demonstrating the required knowledge, skills, and abilities.

- Enterprise data architecture, data modeling, and data mapping

- SQL/PLSQL and data transformation frameworks

- Data modeling tools (Erwin or equivalent)

- Defining and enforcing data governance and platform standards

- Agile methodologies and project delivery frameworks

- Databricks (preferred) or dbt

Knowledge, Skills & Abilities

- Demonstrated ability to design and implement enterprise-scale data solutions and integrations.

- Strong understanding of data architecture patterns, data pipelines, and data lifecycle management.

Advanced SQL proficiency, including:

- --Complex joins

- --Common Table Expressions (CTEs)

- --Window functions

- --Aggregation logic

- --Query performance tuning

Expertise in data modeling methodologies, including:

- --Dimensional modeling (Kimball)

- --Normalization techniques

- --OLTP vs. OLAP design principles

- Experience working in complex, multi-program enterprise environments.

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