Databricks Architect

• Current, hands-on development experience
• Advanced proficiency in SQL and Python/PySpark
• • years of experience in data architecture, data engineering, or platform engineering roles, with at least 3+ years focused on Databricks platform architecture.
• Expert-level knowledge of Databricks platform components: Unity Catalog, Delta Lake, Delta Live Tables, Workflows, SQL Warehouses, MLflow, and Databricks SQL.
• Deep expertise in Unity Catalog governance, including metastore design, catalog/schema strategies, permission models, data lineage, and multi-workspace/multi-cloud patterns.
• Strong architectural background in cloud platforms (Azure, AWS, or Google Cloud Platform), including storage services, identity management (Azure AD, AWS IAM), networking, and security best practices.
• Proven experience designing enterprise-scale data architectures, including medallion/multi-hop architectures, data mesh patterns, domain-driven design, and data product frameworks.
• Hands-on experience with infrastructure-as-code (Terraform, ARM templates, CloudFormation) for platform configuration and governance automation.
• Strong understanding of DevOps practices, CI/CD pipelines, version control strategies, and automated testing for data platforms.
• Experience with performance tuning, cost optimization, and capacity planning for large-scale data platforms.

The profile that fits best is someone who still writes PySpark and Databricks code day to day. That means Unity Catalog administration they’ve done themselves, Terraform, and ideally SQL Server change tracking or CDC into Databricks.