Product Data Architect - Evinova

AstraZeneca•Gaithersburg, MD

1d•Hybrid

About The Position

Evinova is a health-tech business focused on accelerating better health outcomes by advancing digital transformation across the life sciences sector. By combining science-based expertise, evidence-led rigor, and deep human insight, we design digital solutions that enable healthcare to work better for everyone. Operating at the intersection of healthcare, technology, data, and analytics, we are helping unlock the full potential of digital health, transforming how clinical research is conducted, how care is delivered, and how patients experience healthcare. Our solutions are built to scale, driving efficiency, improving decision-making, and ultimately delivering better outcomes for patients worldwide. At Evinova, we are driven by a shared purpose to transform health through data and digital innovation. Our teams collaborate across disciplines to solve complex challenges, continuously learning and evolving in a fast-paced, high-impact environment. We also recognize the importance of flexibility and balance. Our ways of working support both individual needs and team collaboration. To foster connection and collaboration, employees are expected to work from the office three days per week, creating opportunities for in-person teamwork, innovation, and meaningful connection. Role Summary: 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.

Requirements

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

Nice To Haves

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.

Responsibilities

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

Benefits

The annual base pay for this position ranges from $165,656.80 - $ 217,424.55 USD.
Base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience.
In addition, our positions offer a short-term incentive bonus opportunity; eligibility to participate in our equity-based long-term incentive program.
Benefits offered included a qualified retirement program [401(k) plan]; paid vacation and holidays; paid leaves; and, health benefits including medical, prescription drug, dental, and vision coverage in accordance with the terms and conditions of the applicable plans.
Additional details of participation in these benefit plans will be provided if an employee receives an offer of employment.

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