Databricks Architect

STAFFXPERT LLC is seeking a Databricks Architect on behalf of our client in the United States. This role is ideal for a highly skilled data professional with expertise in modern data platforms, cloud-based data engineering, and Databricks architecture. The selected candidate will lead the design and implementation of scalable data solutions, establish data quality standards, and develop reusable frameworks that support enterprise-wide analytics and data governance initiatives., Design and implement Medallion Architecture (Bronze, Silver, Gold) using Delta Lake and Unity Catalog. Define and establish robust data quality frameworks utilizing Lakeflow Declarative Pipelines. Develop scalable and reusable data ingestion, transformation, and validation patterns using PySpark, Auto Loader, Databricks Notebooks, and shared libraries. Architect and optimize end-to-end data pipelines for performance, reliability, and maintainability. Implement and maintain CI/CD processes leveraging Databricks Asset Bundles, Git, and industry best practices. Establish data governance, security, and metadata management standards within the Databricks ecosystem. Collaborate with cross-functional teams, including data engineers, analysts, architects, and business stakeholders, to deliver high-quality data solutions. Provide technical leadership and guidance on scalable cloud data platform architecture.

Proven experience designing and implementing solutions on the Databricks platform. Strong expertise in Delta Lake, Unity Catalog, PySpark, and SQL. Hands-on experience with Auto Loader, Lakeflow Declarative Pipelines, and enterprise data processing frameworks. Deep understanding of data architecture, data modeling, ETL/ELT processes, and data governance principles. Experience implementing CI/CD pipelines using Git-based version control and deployment practices. Strong analytical, problem-solving, and communication skills. Ability to work effectively in a collaborative, fast-paced environment. Preferred Qualifications Experience architecting large-scale cloud data platforms and analytics ecosystems. Experience leading data modernization, migration, or cloud transformation initiatives. Knowledge of enterprise data governance, security, and compliance best practices. Prior experience mentoring engineering teams and defining data platform standards.