Databricks Architect

Must Have Technical/Functional Skills
The information below covers the role requirements, expected candidate experience, and accompanying qualifications.
10+ years of experience in Data Engineering and Data Architecture.5+ years of hands-on experience with Databricks, PySpark, and Apache Spark.Strong expertise in - Databricks Lakehouse Architecture, Delta Lake, Unity Catalog, Delta Live Tables (DLT), Databricks Workflows, Medallion ArchitectureExperience designing enterprise-scale analytics and data platforms.Expert-level proficiency in PySpark and Spark SQL.Advanced SQL development and query optimization skills.Strong understanding of batch and streaming architectures.Experience with data warehousing, ETL/ELT, and large-scale data processing.Expertise in dimensional, relational, and analytical data modeling.Experience implementing data governance, data quality, and metadata management solutions.Knowledge of CI/CD practices, Git, DevOps, and Infrastructure as Code (Terraform preferred).Experience establishing architectural standards and engineering best practices.Roles & ResponsibilitiesArchitect and design scalable, secure, and high-performance data platforms using Databricks and AWS.Lead solution design, data modeling, and enterprise data architecture initiatives.Design and optimize batch and real-time data pipelines using Databricks, PySpark, and Delta Lake.Partner with business and technology stakeholders to define requirements and deliver strategic data solutions.Establish standards for data governance, security, quality, performance, and operational excellence.Provide technical leadership, mentoring, and architectural guidance to engineering teams. xzbcwsv Drive cloud modernization, platform optimization, and data transformation initiatives.