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Senior Databricks Platform Engineer
Build and operate secure Databricks platforms for a global insurance and asset management company. The role covers cloud infrastructure, governance, reliability, and AI workloads.
Сипаттама
- Design and operate enterprise Databricks platforms across cloud environments.
- Deploy Databricks workspaces, clusters, and platform components on Azure and/or AWS.
- Maintain scalable, secure, and highly available Databricks environments.
- Set platform standards, architecture patterns, and operational practices.
- Manage Unity Catalog, Delta Lake, and workspace governance.
- Handle platform lifecycle management, upgrades, and capacity planning.
- Provision infrastructure with Terraform and automate deployments and configuration management.
- Design networking, private connectivity, and secure integrations.
- Implement backup, disaster recovery, and high availability.
- Improve cloud resource use and manage platform costs.
- Apply enterprise security controls and compliance requirements.
- Configure role-based access and least-privilege models.
- Manage secrets, key vault integrations, and encryption standards.
- Set up monitoring, audit logs, and governance controls.
- Support regulatory and security audits.
- Monitor platform health, availability, and performance.
- Build observability for infrastructure and data workloads.
- Troubleshoot platform, networking, and workload problems.
- Create operational runbooks and support processes.
- Lead root-cause analysis and remediation.
- Work with data, AI, and cloud infrastructure teams.
- Advise on platform architecture and operational excellence.
- Create engineering standards and reusable automation patterns.
- Mentor engineers and promote cloud engineering practices.
- Support Databricks AI and machine learning environments.
- Enable MLflow experimentation, model tracking, and deployment.
- Support Mosaic AI, Vector Search, Feature Store, and RAG architectures.
- Assist teams building generative AI and large language model solutions.
- Develop infrastructure and governance for AI workloads.
- Assess new Databricks AI capabilities and recommend adoption strategies.
Талаптар
- Bachelor’s degree in computer science, information technology, engineering, or a related field.
- At least five years of cloud, platform, or infrastructure engineering experience.
- At least three years of hands-on experience deploying and administering Databricks environments.
- Experience supporting enterprise cloud platforms on Azure and/or AWS.
- Experience designing secure, scalable, highly available cloud solutions.
- Skills in Databricks administration, Unity Catalog, Delta Lake, workspace management, cluster configuration and optimization, workflows, and job scheduling.
- Knowledge of Microsoft Azure and Amazon Web Services (AWS).
- Terraform experience.
- Experience with Azure DevOps or GitHub Actions.
- CI/CD pipeline experience.
- Scripting skills in PowerShell, Python, or Bash.
- Knowledge of RBAC, private endpoints, VNET/VPC design, encryption and key management, identity federation, and secrets management.
- Experience with 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, Azure Solutions Architect, or AWS Solutions Architect certification.
- Preferred experience implementing enterprise AI and machine learning platforms.
- Preferred experience supporting regulated industries such as insurance or financial services.
- Desired familiarity with Mosaic AI, MLflow, Databricks Model Serving, Vector Search, Feature Store, RAG, large language models, AI governance and responsible AI practices, and AI-enabled data engineering patterns.
Артықшылықтар
- Contractor engagement model (PJ).
- Hybrid work with three days per week in person at the Pinheiros, São Paulo office.
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