Data Architect

Data Architect - AI & Data Products Architect

100% REMOTE

3 month contract + extensions

Must-Have Qualifications

• 10+ years of experience working in Data Modeling & Architecture - Strong experience designing enterprise data models and data architectures.
• Hands-On Technical Experience with SQL expertise, Apache Spark, and working closely with data engineering teams and modern data platforms
• Experience supporting AI/ML initiatives through data architecture (Claude, OpenAI, LangChain, or similar)
• Understanding of data governance, metadata, lineage, and data quality best practices

Plusses:

• Life Sciences, Pharmaceutical, or Healthcare experience.
• Experience supporting drug discovery or research data environments.
• Exposure to Electronic Lab Notebook (ELN) platforms.
• Experience with cloud data platforms (AWS, Azure, or GCP).
• Background designing AI-enabled data products in highly regulated environments.

Overview

A large pharma client is seeking a hands‑on Data Architect to support the design and delivery of AI‑enabled data products within a large‑scale enterprise data platform. This individual will partner closely with product managers, engineering teams, and business stakeholders to design scalable data models, data products, and architecture that support AI/ML and agentic AI use cases. This is not a strategy‑only architecture role. The ideal candidate will be actively involved in designing datasets, data models, and data foundations that enable AI‑driven solutions and intelligent agents across the organization.

Key Responsibilities

• Design and implement scalable enterprise data architectures and data products.
• Create and maintain logical and physical data models that support AI/ML initiatives.
• Design datasets and make them accessible for end users, analytics teams, and AI applications.
• Partner with product managers and business stakeholders to gather requirements and translate them into technical solutions.
• Define governance standards and ensure data quality, metadata management, and compliance best practices.
• Support AI and Agentic AI initiatives by designing data foundations and pipelines that enable intelligent workflows and automation.
• Collaborate with engineering teams to ensure solutions are scalable, maintainable, and aligned with enterprise architecture standards.
• Drive architecture delivery from concept through implementation.

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