Platform Engineer - Databricks and Cloud

Job summary

Job Description: EXL is seeking an experienced Platform Engineer to design, implement, automate and operate cloud infrastructure for large scale analytics and data engineering workloads. This role focuses on building and managing Databricks on AWS, Infrastructure-as-Code, CI/CD automation, platform reliability, and cloud governance.

Qualifications

• Job Description: EXL is seeking an experienced Platform Engineer to design, implement, automate and operate cloud infrastructure for large scale analytics and data engineering workloads.
• The ideal candidate will bring strong hands-on experience across AWS cloud services, Terraform, DevOps practices, and a solid understanding of data engineering platforms, pipelines, and workload orchestration.
• Strong hands-on experience managing AWS infrastructure through Terraform, including networking, security, compute, storage, and IAM services.
• Practical experience working with Databricks on AWS, including workspace administration, compute management, job orchestration, and platform operations.
• Good understanding of data engineering concepts such as ETL/ELT pipelines, data lakes, workflow orchestration, batch processing, and data platform architecture.
• Working knowledge of data engineering ecosystems and

Responsibilities

• Design, build, and manage scalable AWS infrastructure including EC2, EKS, Lambda, API Gateway, VPCs, IAM, Security Groups, Load Balancers, and routing components
• Implement Infrastructure-as-Code (IaC) using Terraform/AWS CDK to automate provisioning, scaling, and environment management
• Set up and manage DevOps pipelines using GitHub, GitHub Actions, CodeBuild, CodeDeploy and ArgoCD to support automated build, test, and deployment workflows.
• Design, deploy, and manage Databricks workspaces, clusters, cluster policies, Unity Catalog, networking, and security integrations on AWS.
• Partner with data engineering teams to enable reliable execution of pipelines, data ingestion frameworks, batch processing, and workflow orchestration.
• Automate deployment and lifecycle management of data platform components, including Databricks jobs, workflows, libraries, secrets, service principals, and environment configurations.
• Collaborate with data engineering teams to support infrastructure components such as AWS Glue, Lambda, Databricks on AWS, DynamoDB, and Redshift.
• Monitor and optimize platform performance, reliability, and cloud costs for data engineering workloads and analytics platforms.
• Troubleshoot platform, connectivity, and workload issues
• Utilize AWS Well-Architected Framework principles to design secure, reliable, cost-efficient, and high-performing solutions
• Implement platform governance, access controls, security standards, and operational best practices across cloud and data platforms.
• Contribute to establishing DevOps best practices, reusable templates, and standard operating procedures across engagements

Certifications

Degrees

Industry

Security clearance