Data Architect

Insight Global; Greater London; Remote; GBP 90,000 - 130,000; Part time

Benefits offered by this job

Remote work

Job summary

Insight Global is seeking a hands-on Data Architect to design and deliver AI-enabled data products within a large-scale enterprise data platform. You will partner with product managers, engineering, and business stakeholders to create scalable data models and data foundations that support AI/ML and agentic AI use cases.

The role requires designing datasets, data models, and data products, ensuring governance, metadata, and data quality standards, and collaborating across teams to enable

Qualifications

• 10+ years of experience in data modeling and architecture in enterprise environments.
• Hands-on SQL, Apache Spark, and collaboration with data engineering teams.
• Experience supporting AI/ML initiatives through data architecture and data foundations.
• Understanding of governance, metadata, lineage, and data quality best practices.

Responsibilities

• Design scalable enterprise data architectures and data products.
• Create and maintain logical and physical data models for AI/ML initiatives.
• Make datasets accessible for end users, analytics teams, and AI apps.
• Partner with product managers to translate requirements into technical solutions.
• Define governance standards and oversee data quality and metadata management.
• Support AI initiatives by designing data foundations and pipelines for intelligent workflows.
• Collaborate with engineering to ensure scalable, maintainable solutions aligned with standards.
• Drive architecture delivery from concept to implementation.

Skills

Data modeling

Data architecture

SQL

Apache Spark

AI/ML data architecture

Data governance

Tools

AWS

Azure

GCP

Job description

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.