Lead Databrics Solution & Platform Architect

Role Overview

We are looking for an experienced Databricks Solution Architect who will lead the design and implementation of enterprise-scale data platforms on Databricks. The role combines data architecture expertise with strong platform and cloud engineering skills, covering both business use cases and the underlying Databricks infrastructure.

The architect will be responsible for defining the target architecture, establishing platform foundations, and ensuring the environment is secure, scalable, governed, and production-ready. This includes designing Databricks workspaces, cloud infrastructure, security controls, CI/CD processes, data governance, and operational standards while supporting delivery teams in implementing data ingestion, transformation, and analytics workloads.

Key Responsibilities

• Design end-to-end Databricks platform and data architecture on AWS.
• Define and implement workspace strategy, environment separation (DEV/TEST/PROD), networking and security architecture.
• Establish Unity Catalog, data governance, access control, and data-sharing standards.
• Design Infrastructure as Code (Terraform), CI/CD and deployment processes.
• Configure monitoring, observability, cost management and operational controls.
• Define scalable ingestion and transformation patterns using Databricks capabilities.
• Support platform qualification and production-readiness activities, including regulated (GxP) environments where applicable.
• Collaborate with cloud, security, infrastructure and business stakeholders.
• Provide technical leadership and architectural governance across delivery teams.
• Lead architecture reviews, design decisions, and technology standards.

Required Experience

• Strong hands-on experience with Databricks architecture and administration.
• Experience designing cloud-native data platforms on AWS.
• Deep knowledge of Unity Catalog, security, IAM, networking, cluster policies and governance.
• Experience with Terraform and DevOps/CI-CD practices.
• Knowledge of data engineering frameworks and scalable data architecture patterns.
• Ability to lead both platform foundation work and data solution design.
• Experience in regulated industries (Life Sciences, Pharma, Healthcare) is a plus