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A Data Architect is responsible for designing and implementing scalable, secure, and efficient Databricks solutions that meet client requirements. This role requires a deep understanding of data engineering, including data warehousing, ETL, and data governance.
">Responsibilities- Design and implement: Scalable, secure, and efficient Databricks solutions that meet client requirements.
- Develop data pipelines, architect data lakes, and implement data warehousing solutions using Databricks.
- Collaborate with data scientists and analysts to develop and deploy machine learning models and analytics solutions on Databricks.
- Optimize Databricks cluster performance, ensuring efficient resource utilization and cost-effectiveness.
- Implement Databricks security features, ensure data governance, and maintain compliance with industry regulations.
- Work closely with clients to understand their business requirements, provide technical guidance, and deliver high-quality Databricks solutions.
- Stay up-to-date with the latest Databricks features, best practices, and industry trends, and share knowledge with the team.
- 5+ years of experience working with Databricks, including platform architecture, data engineering, and data analytics.
- Proficiency in languages such as Python, Scala, or Java, and experience with Databricks APIs, Spark, and Delta Lake.
- Strong background in data engineering, including data warehousing, ETL, and data governance.
- Proven experience leading technical teams, mentoring junior engineers, and driving technical initiatives.
- Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal stakeholders.
- Databricks Certified Professional or similar certifications.
- Experience working with cloud platforms such as AWS, Azure, or GCP.
- Knowledge of machine learning concepts and experience with popular ML libraries.
