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Global insurance and asset management company seeks a responsible, organized, dynamic and team-oriented person
- We are seeking a highly skilled Cloud Data Platform Engineer to design, deploy, administer, and optimize enterprise-scale Databricks platforms across cloud environments
- This role will be responsible for building and maintaining secure, scalable, and reliable data platforms that enable analytics, machine learning, and AI-driven business solutions
- The ideal candidate combines expertise in cloud infrastructure, platform engineering, data technologies, security, automation, and Databricks administration
- Experience with Databricks AI capabilities, including Generative AI, Vector Search, MLflow, and Mosaic AI, is highly desirable
- Key ResponsibilitiesDatabricks Platform Engineering: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
- Cloud Infrastructure & Automation:Provision infrastructure using Infrastructure-as-Code tools such as Terraform
- 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
- Security & Governance: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
- Platform Operations & Reliability: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
- Collaboration & Technical Leadership: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
- AI & Advanced Analytics Support (Preferred)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