Senior Databricks Architect with DBT
Required Experience
12+ years of experience in Data Architecture, Data Engineering, or Enterprise Data Platforms.
Strong hands-on experience with Databricks, including Delta Lake, Unity Catalog, and Databricks Workflows.
Strong expertise in Apache Spark (PySpark), Python, SQL, and dbt.
Experience designing scalable Data Lakehouse architectures and enterprise data models.
Experience building and optimizing ETL/ELT pipelines using Databricks and dbt.
Strong understanding of data governance, security, and access management.
Hands-on experience with at least one cloud platform: AWS, Azure, or Google Cloud Platform.
Experience integrating enterprise applications and third-party systems using MuleSoft.
Excellent problem-solving, communication, and stakeholder management skills.
Job Decription:
8+ years of experience in Platform Engineering, Cloud Engineering, or Data Platform Administration.
Strong hands-on expertise in Databricks Workspace Administration, Unity Catalog, Cluster Policies, and enterprise Data Governance.
Experience configuring and managing access control, permissions, security, and compliance across the Databricks platform.
Proficiency in platform performance tuning, monitoring, troubleshooting, and cost optimization.
Experience implementing advanced Databricks capabilities, including Genie, Lakehouse Apps, Delta Lake, and Lakehouse Architecture.
Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (Google Cloud Platform).
Strong experience with Infrastructure as Code (Terraform), CI/CD pipelines, automation, and Git/DevOps best practices.
Proficiency in scripting using Python, Bash, or PowerShell.
Experience with monitoring and observability tools for platform health and performance.
Excellent analytical, problem-solving, communication, and stakeholder management skills.
Relevant Databricks or cloud platform certifications is huge plus
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