Data Platform Architect Lead

Key Responsibilities

• Define the target-state architecture for the enterprise data lakehouse platform across Azure, Databricks, storage, transformation, governance, and consumption.
• Lead platform design for Databricks, Unity Catalog, MLflow, dbt, and shared data/ML services.
• Own the governance model for permissions, roles, access controls, lineage, and catalog structures across the platform.
• Establish standards for development, test, and production environments to ensure consistency and reliability.
• Drive platform automation for governance checks, workflow controls, monitoring, deployment, and operational tasks.
• Enable users and domain teams through reusable templates, platform standards, and self-service patterns.
• Support modern data product and data mesh ways of working, balancing domain autonomy with enterprise controls.
• Partner with engineering, analytics, governance, and business teams to align platform evolution with business priorities.
  
  

• Strong experience in data architecture, platform architecture, or enterprise data engineering.
• Deep hands-on expertise with Databricks.
• Strong experience with Microsoft Azure, especially Azure-based data platform architecture and lakehouse design.
• Deep knowledge of Unity Catalog, including permissions, roles, access models, lineage, and governance controls.
• Experience with MLflow for experiment tracking, lifecycle management, and ML platform governance.
• Strong experience with dbt and modern transformation practices.
• Strong understanding of data lakehouse architecture, platform environments, and operational controls.
• Strong command of SQL and Python.
• Experience with automation of platform, governance, and operational processes.
  
  

• Experience with data mesh or federated data operating models.
• Familiarity with Power BI, Snowflake, Fabric, or similar enterprise ecosystems.
• Experience with Terraform, CI/CD, or infrastructure automation.
• Exposure to AI/ML governance and enterprise platform controls.
• Experience in large or regulated enterprise environments.
  
  

• 8+ years of experience in data architecture, data platforms, or related roles.
• Proven experience designing and scaling Databricks-based platforms on Microsoft Azure.
• Strong experience with enterprise lakehouse architecture, governance, and platform enablement.
• Experience driving platform standards, user adoption, and operating model maturity.
• Strong ability to work across architecture, engineering, governance, and business teams.
• Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or a related field.