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# Product Data Architect - Evinova

- **Company:** AstraZeneca plc
- **Location:** Gaithersburg, MD, United States
- **Experience:** Expert
- **Salary:** $87,100.0 - $157,450.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computing Platforms, Computer Engineering, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, Information Sciences, Python (Programming Language), NoSQL, Software Architecture, Standard Sql, Verification and Validation (Software), Data Streaming, System Testing, Large Language Models, Generative AI, Data Layers, Information Technology, Data Management, Data Pipelines, GXP
- **Published:** August 18, 2026
- **Apply:** https://www.careerjet.com/job/usad2648a1561be696fd1a5b6595335742/eaa

## About the Role

Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Information Science, or a related field
8+ years of experience in data architecture, data engineering, or platform architecture roles
Proven experience owning data architecture for complex products or product suites
Strong experience in data modeling and data design
Proficiency in Python
Experience working with SQL and NoSQL databases
Hands-on experience building and managing ETL processes and data pipelines
Demonstrated ability to make architectural decisions with product-level impact
Strong collaboration skills with Product and Engineering teams
A data-driven mindset, with experience defining metrics and using insights to guide decisions
Preferred Qualifications
Experience architecting data layers for AI/ML-powered products - especially LLM pipelines, RAG architectures, vector databases, or embedding strategies.
Familiarity with GxP software validation, computerised system validation (CSV), or regulated-industry quality practices.
Background in life sciences, health-tech, or clinical-trial technology.
Experience working with geographically distributed teams and external vendor squads.
Experience operating within a Data Owner / Data Steward governance model.
Experience defining reference architectures reused across multiple products.
Prior experience mentoring senior engineers or architects.

## Description

As a Product Data Architect at Evinova, you will shape the data architecture behind our AI-powered products, including Study Designer and AI Document Authoring. You'll design scalable, secure, and high-quality data solutions that enable smarter, more connected clinical trials.
Working closely with Product and Engineering teams, you'll define data models, integration patterns, and standards that support both current delivery and future innovation-especially across AI, LLM, and RAG-driven capabilities in a regulated environment.
This is a high-impact role where you'll help build the data foundations that power the next generation of digital health solutions.
What You'll Do:
Shape Data Architecture for AI-Powered Products
Design and evolve data models that power our AI-native products
Build and guide architectures supporting LLMs, generative AI, and RAG pipelines
Define scalable data flows, integration patterns, and interfaces across products
Establish reusable data patterns to support long-term product growth
Ensure Quality, Compliance, and Scalability
Drive consistency and interoperability across our product ecosystem
Align data architecture with regulatory and enterprise standards (including GxP)
Support data governance practices like access, retention, and auditability
Identify risks and continuously improve data architecture and performance
Use Data to Drive Better Decisions
Define metrics and dashboards to monitor data quality and system health
Turn insights into actionable improvements for product and engineering teams
Promote a strong data quality mindset across teams
Collaborate and Deliver Across Teams
Partner with Product and Engineering to bring scalable data solutions to life
Work closely with global teams and external partners to guide implementation
Stay hands-on when needed-supporting design, troubleshooting, and delivery
Lead and Elevate Data Excellence
Mentor engineers and help set best practices for data architecture
Contribute to a shared vision across teams and geographies
Help define how data supports AI-driven product innovation at scale
What Success Looks Like:
Data models and interfaces are clear, scalable, and widely adopted across teams
Product teams move faster with fewer data-related blockers or rework
Data architecture evolves seamlessly as products, AI capabilities, and usage grow
LLM and RAG pipelines are reliable, transparent, and meet both technical and regulatory standards
You are seen as a trusted partner by Product and Engineering leadership


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