Databricks Architect

Solution Design & Implementation: Architect and implement scalable, secure, and high-performance data solutions on the Databricks platform. Design end-to-end data pipelines, ensuring seamless integration with Databricks and AWS services. Data Integration: Utilize Informatica for ETL processes, ensuring efficient data integration and transformation across various data sources. AWS Expertise: Leverage AWS services such as Glue for data cataloging and ETL, and Lambda for serverless computing to enhance data processing capabilities. Technical Leadership: Lead technical engagements, collaborating with internal teams and client stakeholders. Guide data engineers, analysts, and developers in implementing best practices on Databricks. Optimization & Performance: Optimize Databricks solutions for cost efficiency, performance, and reliability. Implement advanced performance tuning and debugging techniques. Governance & Compliance: Establish and enforce governance, security, and compliance standards within Databricks environments. 8+ years of experience in data architecture, engineering, or analytics roles. 5+ years of experience with modern data architecture principles, including cloud platforms (AWS, Azure, GCP). 3+ years of recent hands-on experience with Databricks. Proficiency in SQL, Python, and ETL tools such as Informatica. Expert knowledge of Databricks architecture, including data sharing, performance optimization, and data security. Hands-on experience with data modeling, schema design, and ELT pipeline development. Understanding of cloud-native services for data ingestion, transformation, and orchestration. Certifications in Databricks such as Databricks Certified Professional Data Engineer.