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Cloud Data Platform Engineer – Databricks Platform Engineering
Keep IT Simple. Design, deploy, administer, and optimize enterprise-scale Databricks platforms across cloud environments .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, deploying, and optimizing Databricks platforms across cloud environments, with a strong focus on security, scalability, and compliance. Proficient in managing cloud infrastructure using Terraform and implementing AI and machine learning solutions within enterprise settings.
Highest-signal resume keywords
Databricks AdministrationCloud EngineeringTerraformMicrosoft AzureAmazon Web Services
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Databricks WorkflowsCluster Configuration and OptimizationIdentity and Access ManagementRBACPerformance TuningCapacity ManagementPython ScriptingPowerShell ScriptingBash ScriptingCI/CD Pipelines
Soft Skills
Technical GuidanceMentoringCollaboration
Tools & Technologies
Azure DevOpsGitHub ActionsAzure MonitorCloudWatchLog Analytics
Certifications & Qualifications
Databricks Certified Platform AdministratorDatabricks Certified Data Engineer ProfessionalAzure Administrator AssociateAWS Solutions Architect
Industry Keywords
Enterprise AIMachine Learning PlatformsRegulated EnvironmentsInsuranceFinancial Services
Tech Stack
Tools & technologiesAWSAzureCloudPythonTerraformUnityVault
About the role
Key responsibilities & impact- Design, deploy, administer, and optimize enterprise-scale Databricks platforms across cloud environments
- Design and deploy Databricks workspaces, clusters, and platform components in Azure and/or AWS
- Build and maintain scalable, secure, and highly available Databricks environments
- Establish platform standards, architecture patterns, and operational best practices
- Configure and manage Unity Catalog, Delta Lake, and workspace governance frameworks
- Implement platform lifecycle management, upgrades, and capacity planning
- Provision infrastructure using Terraform and automate platform deployments and configuration management
- Design networking, private connectivity, and secure integration patterns
- Implement backup, disaster recovery, and high-availability solutions
- Optimize cloud resource utilization and manage platform costs
- Implement enterprise security controls and compliance requirements
- Configure role-based access controls and least-privilege access models
- Manage secrets, key vault integrations, and encryption standards
- Establish monitoring, audit logging, and governance controls
- Support regulatory and security audits
- Monitor platform health, availability, and performance
- Develop observability solutions for infrastructure and data workloads
- Troubleshoot platform, networking, and workload issues
- Create operational runbooks and support processes
- Lead root-cause analysis and remediation efforts
- Partner with Data Engineers, Data Scientists, AI Engineers, and Cloud Infrastructure teams
- Provide technical guidance on platform architecture and operational excellence
- Develop engineering standards and reusable automation patterns
- Mentor engineers and promote cloud engineering best practices
- Support Databricks AI and machine learning environments
- Enable MLflow experimentation, model tracking, and deployment capabilities
- Support Mosaic AI, Vector Search, Feature Store, and RAG architectures
- Assist teams implementing Generative AI and Large Language Model solutions
- Develop infrastructure and governance frameworks supporting AI workloads
- Evaluate new Databricks AI capabilities and recommend adoption strategies
Requirements
What you’ll need- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
- 5+ years of experience in cloud engineering, platform engineering, or infrastructure engineering
- 3+ years of hands-on experience deploying and administering Databricks environments
- Experience supporting enterprise cloud platforms in Azure and/or AWS
- Experience designing highly available, secure, and scalable cloud solutions
- Databricks Administration, Unity Catalog, Delta Lake, Workspace Management, Cluster Configuration and Optimization, Databricks Workflows, Job Scheduling, Identity and Access Management
- Microsoft Azure and Amazon Web Services (AWS)
- Terraform
- Azure DevOps or GitHub Actions
- CI/CD Pipelines
- PowerShell, Python, or Bash scripting
- RBAC, Private Endpoints, VNET/VPC Design, Encryption and Key Management, Identity Federation, Secrets Management
- Databricks Monitoring, Azure Monitor, CloudWatch, Log Analytics, Performance Tuning and Capacity Management
- Preferred: Databricks Certified Platform Administrator; Databricks Certified Data Engineer Professional; Azure Administrator Associate or Azure Solutions Architect certification; AWS Solutions Architect certification
- Preferred experience implementing enterprise AI and machine learning platforms
- Preferred experience supporting regulated environments such as Insurance or Financial Services
- Desired exposure to Databricks Mosaic AI, MLflow, Databricks Model Serving, Databricks Vector Search, Feature Store, Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), AI Governance and Responsible AI Practices, and AI-enabled Data Engineering Patterns
Benefits
Comp & perks- Modelo de contratação PJ
- Trabalho híbrido, com 3 dias por semana presenciais no escritório de Pinheiros/SP