Databricks Architect

• 10+ years of experience in Data Engineering and Data Architecture. \n

• 5+ years of hands-on experience with Databricks, PySpark, and Apache Spark. \n

• Strong expertise in - Databricks Lakehouse Architecture, Delta Lake, Unity Catalog, Delta Live Tables (DLT), Databricks Workflows, Medallion Architecture \n

• Experience designing enterprise-scale analytics and data platforms. \n

• Expert-level proficiency in PySpark and Spark SQL. \n

• Advanced SQL development and query optimization skills. \n

• Strong understanding of batch and streaming architectures. \n

• Experience with data warehousing, ETL/ELT, and large-scale data processing. \n

• Expertise in dimensional, relational, and analytical data modeling.

• Experience implementing data governance, data quality, and metadata management solutions. \n

• Knowledge of CI/CD practices, Git, DevOps, and Infrastructure as Code (Terraform preferred). \n

• Experience establishing architectural standards and engineering best practices. \n

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Roles & Responsibilities

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• Architect and design scalable, secure, and high-performance data platforms using Databricks and AWS. \n

• Lead solution design, data modeling, and enterprise data architecture initiatives. \n

• Design and optimize batch and real-time data pipelines using Databricks, PySpark, and Delta Lake. \n

• Partner with business and technology stakeholders to define requirements and deliver strategic data solutions. \n

• Establish standards for data governance, security, quality, performance, and operational excellence. \n

• Provide technical leadership, mentoring, and architectural guidance to engineering teams. \n

• Drive cloud modernization, platform optimization, and data transformation initiatives. \n

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