Role Summary: The Databricks Architect is responsible for designing, implementing, and governing enterprise-scale data platforms on Databricks. The role focuses on data architecture, cloud integration, data engineering best practices, analytics enablement, and platform optimization across Azure, AWS, or Google Cloud Platform environments. Responsibilities Design and implement scalable data lakehouse architectures using Databricks. Define enterprise data models, governance standards, and security controls. Lead migration of legacy data warehouses and ETL workloads to Databricks. Architect batch and real-time data processing solutions using Spark. Optimize performance, scalability, reliability, and cost efficiency. Collaborate with business stakeholders, data engineers, data scientists, and cloud architects. Establish CICD, monitoring, and operational best practices for data platforms. Provide technical leadership and mentor engineering teams. Required Skills 8+ years of data engineering and data platform experience. 3+ years of hands-on Databricks architecture experience. Strong expertise in Apache Spark, PySpark, SQL, and Delta Lake. Experience with Azure Databricks, AWS Databricks, or Google Cloud Platform Databricks. Strong expertise in streaming platforms: Google Cloud Platform PubSub, Azure Event Hubs, AWS Kinesis, Apache Kafka Hands-on experience with producerconsumer architecture decisions and trade-offs. Knowledge of data lakehouse architecture and data governance. Experience with data integration tools and orchestration frameworks. Strong understanding of security, access management, and compliance requirements. Preferred Skills Databricks Certified Data Engineer Professional or equivalent. Experience with Unity Catalog, Delta Live Tables, and Databricks Workflows. Experience with Power BI, Tableau, or other BI platforms. Knowledge of DataOps, DevOps, and MLOps practices. Education Bachelors degree in Computer Science, Engineering, Information Systems, or related field. Masters degree preferred.
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