Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related ###
Experience:
6-15 Yrs
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Full description
Work on diverse customer-facing Big Data projects, including reference architectures, how-to guides, and MVP development
Lead end-to-end design, build, and deployment of large-scale big data and AI solutions
Provide architectural guidance to drive Databricks adoption across business teams
Design and manage Databricks infrastructure, connectivity, integration patterns, and Unity Catalog migrations
Manage clusters, networking, platform engineering, and data governance initiatives
Collaborate closely with platform engineering teams to implement Databricks services effectively
Evaluate and adopt new Databricks features, including Serverless capabilities
Design and implement integrations between Databricks and third-party tools such as Collibra and data quality platforms
Apply AWS administration and architecture expertise to optimize cloud resources and Databricks integrations
Implement Unity Catalog for strong data governance, security, and lineage tracking
Promote and implement CI/CD practices for Databricks solution deployments
Contribute to data mesh architecture by enabling decentralized data ownership and access
Communicate Databricks analytics capabilities to help teams derive actionable insights
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Required Knowledge, Skills, and Abilities
+ Strong experience with AWS cloud services and architecture
+ Excellent documentation and whiteboarding skills to explain complex concepts
+ Deep knowledge of Databricks services, including Unity Catalog and Serverless Databricks
+ Proven experience migrating from Databricks Classic to Lakehouse architecture using Delta and/or Delta Live Tables
+ Strong collaboration skills with the ability to work across teams and functions
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