The Databricks Administrator will be responsible for the overall health, security, and performance of the Databricks platform. This includes managing user access, implementing and enforcing data governance policies, optimizing cluster resources, and ensuring data sensitivity policies are effectively applied across the data lakehouse. The administrator will also be crucial in identifying, reporting, and resolving discrepancies within the platform's operation and configuration.
Key Responsibilities
User Provisioning and Management :
Onboard and offboard users, groups, and service principals within Databricks, including integration with identity providers (IdPs) like Azure Active Directory or Okta via SCIM.
Manage user roles and entitlements at both the account and workspace levels (Account Admins, Workspace Admins, Metastore Admins, etc.).
Implement and maintain role-based access control (RBAC) and attribute-based access control (ABAC) to ensure appropriate data and resource access.
Data Lake Governance (Unity Catalog focus) :
Configure and manage Unity Catalog metastores, catalogs, schemas, and tables.
Define and enforce data access policies (e.G., table-level, column-level, row-level security) using Unity Catalog.
Manage data lineage and auditing capabilities to track data flow and usage.
Collaborate with data owners and stakeholders to define data quality standards and ensure data integrity.Implement data retention and lifecycle management policies.
Aligning Data Sensitivity Policy to Enforceable Data Governance :
Translate organizational data classification and sensitivity policies into technical controls within Databricks.
Utilize features like data masking and encryption to protect sensitive information.
Ensure compliance with regulatory requirements (e.G., GDPR, HIPAA, CCPA) by implementing appropriate security measures.
Conduct regular security audits and vulnerability assessments.
Managing Cluster and Budget Policies :
Define and implement compute policies to control cluster creation, configuration, and resource usage, ensuring cost optimization.
Monitor and manage serverless budget policies to attribute usage to specific teams or projects.
Optimize cluster configurations for performance and cost-effectiveness, leveraging features like auto-scaling and auto-termination.
Manage cluster pools to reduce startup times and improve resource allocation.
Reporting and Addressing Discrepancies :
Monitor Databricks platform health, performance, and resource utilization.
Identify and troubleshoot issues related to user access, data availability, cluster performance, and policy violations.
Generate reports on platform usage, costs, security incidents, and compliance.
Investigate and resolve discrepancies in data, reports, or system behavior in collaboration with data engineers, data scientists, and other teams.
Develop and maintain comprehensive documentation of configurations, procedures, and best practices.
Collaboration and Support :
Provide technical support and guidance to Databricks users, data engineers, and data scientists.
Collaborate with cloud infrastructure teams (AWS, Azure, GCP) to manage underlying cloud resources.
Stay up-to-date with the latest Databricks features, best practices, and industry trends.
Technical Skills :
Databricks Platform Expertise :
Deep understanding of Databricks architecture, workspaces, and key components (Unity Catalog, Delta Lake, Spark, SQL Analytics).Proficiency in Databricks administration console and APIs.
Experience with Databricks Workflows, Jobs, and Delta Live Tables (DLT) for orchestration and pipeline management.
Cloud Platform Knowledge :
Strong experience with AWS and its relevant services.
Data Governance & Security :
Solid understanding of data governance principles, data classification, and data lifecycle management.
Experience implementing security controls, access policies (RBAC), and encryption.
Familiarity with compliance standards (GDPR, HIPAA, CCPA) and auditing practices.
Programming & Scripting :
Proficiency in SQL for data querying and access control.
Deep expertise in Terraform is essential, extending beyond basic knowledge to managing complex, multi-project infrastructure. This includes hands-on experience with custom Terraform modules crucial for Data Mesh orchestration.
Scripting skills (e.G., Python, Terraform) for automation and administrative tasks.
Familiarity with Spark and PySpark concepts for troubleshooting and optimization.
Identity and Access Management (IAM) :
Experience with enterprise identity providers (e.G., Azure AD, Okta, Active Directory) and SCIM provisioning.
Networking Concepts :
Understanding of network security, VPNs, VPCS, private links, VPC peering, and connectivity within cloud environments.
Monitoring & Logging Tools :
Experience with monitoring tools (e.G., Datadog, Observe, cloud-native monitoring) for platform health and performance.
Soft Skills
Problem-Solving and Troubleshooting : Ability to diagnose and resolve complex technical issues efficiently.
Communication : Excellent verbal and written communication skills to interact with technical and non-technical stakeholders.
Attention to Detail : Meticulous in configuring policies, managing access, and ensuring data integrity.
Proactive and Self-Driven : Ability to anticipate issues, recommend solutions, and continuously improve the platform.
Collaboration : Work effectively with cross-functional teams (data engineers, data scientists, security teams).
Analytical Thinking : Ability to analyze data and system logs to identify trends and discrepancies.
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Platform Engineer • Hyderabad, Republic Of India, IN
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