Sr. AWS infra engineer

Note -Client not want a data engineer or data scientist . Need AWS infra engineer

\Position: Sr. AWS infra engineer

Location: either dallas, Texas or Columbus, Ohio or Minneapolis, Minnesota

Onsite: 4 days a week

Interview process: spark hire, then video interview, then face to face (MUST FACE TO FACE IN ANY OF THOSE MARKETS AS THE TEAM SITS ALL OVER)

Contract only on W2 

Must have: AWS, Kubernetes, Lambdas, EC2, CI/CD experience, Terraform, Athena, Glue

What we need:

•      An engineer who has spent the majority of their career building, operating, and maintaining cloud infrastructure on AWS — not just using cloud services for data processing.

•      Hands-on Kubernetes administration: deploying clusters, managing nodes, networking (ingress, CNI), RBAC, persistent storage, and troubleshooting production issues.

•      Experience with infrastructure-as-code - primarily Terraform - to provision and manage AWS resources programmatically

•      CI/CD pipeline ownership: building and maintaining pipelines using Azure DevOps or equivalent tools

•      Security-first mindset: IAM policies, security groups, VPCs, audit logging, vulnerability remediation within SLAs

•      Ability to support Data Science and AI/ML platform infrastructure (e.g., Shakudo on EKS, SAS Viya on Kubernetes) not build the models, but run the platform they sit on.

•      Experience with AWS services: EKS, ECR, SageMaker (infra layer), Lambda, Athena, Glue - specifically managing and operating them, not just calling APIs from notebooks

•      Database infrastructure support: Athena, Oracle, MySQL, Postgres — connection management, performance, security, not DBA-level tuning.

What we DON’T need:

•      A Data Scientist or ML Engineer who has ''used AWS'' - we need infrastructure operators, not model builders.

•      A Data Engineer who knows Spark, Glue jobs, or ETL pipelines — that is not this role

•      A Cloud Developer who writes Lambda functions or application code — we need platform engineers.

•      Anyone whose primary Kubernetes experience is running kubectl commands in a managed service without understanding the underlying cluster architecture.

•      Candidates who list ''Kubernetes'' on their resume but cannot explain what a DaemonSet, Ingress controller, or PersistentVolumeClaim is.

•      Candidates with AWS certifications but no hands-on production infrastructure experience.

What will this platform engineers do in my team:

This is a Platform Engineering role embedded in the Data Science division. The team runs critical data and AI/ML infrastructure on AWS, including Shakudo (a data science platform), SAS Viya - all running on Kubernetes (EKS). The engineer''s job is to keep that infrastructure running, secure, scalable, and automated.

Day-to-Day Responsibilities Include:

•      Manage and operate AWS EKS clusters that host Shakudo and SAS Viya — currently supporting 25+ active prototypes, growing to 60+ by end of 2026.

•      Build and maintain CI/CD pipelines using Azure DevOps for deploying data science environments and platform updates

•      Provision and manage AWS infrastructure using Terraform - VPCs, EKS node groups, IAM roles, ECR, RDS instances.

•      Manage container image lifecycle via Amazon ECR - building, versioning, scanning for vulnerabilities.

•      Set up and maintain AWS accounts for the Data Science platform, including IAM, cost controls, and security guardrails.

•      Respond to infrastructure incidents within SLA - on-call rotation, root cause analysis, post-mortems.

•      Perform Kubernetes cluster upgrades, node patching, and security remediation.

•      Support Data Scientists by unblocking infrastructure issues - not writing their code, but ensuring their compute and storage works.

•      Conduct knowledge transfer sessions within the platform team - documentation, runbooks, workshops

•      Collaborate with Network, Database, Architecture, and Security teams.