Principal Engineer Big Data Platform

As a handson container and infrastructure engineer you are responsible for design implement and support our global hybrid cloud container platform using Kubernetes and Google Cloud Platform (GCP) Anthos and AWS.

Candidate should have expertise in building virtualization platforms of storage network and compute for large scale high availability factory manufacturing type workloads. Proven Experience in setting up continuous integration of source code pipelines using Bitbucket Jenkins Terraform Ansible etc. is required. Ability to build continuous deployments using Docker Artifactory Spinnaker etc. is required with a strong advocate of DevOps principles. Candidate should be passionate about developing and delivering modern softwareasaservice (SaaS) design principles. This position requires partnering with various Western Digital manufacturing engineering and IT teams in understanding factorycritical workloads and designing solutions.

Big data platform BDP team provides selfservice data and application platforms to enable machine learning (ML) capabilities to engineering and data science community. The ideal candidate should be passionate about working with various cloud tools to handle various Service Level Agreements (SLA). Candidate should be versatile to experiment with failfast approach to adopt to new technologies and natural troubleshooting capabilities. Communication with internal customers external vendors and coworkers in a clear and professional manner is expected.

Job Responsibilities

• Work in global team to design implement and operate our global hybrid cloud container platform (Kubernetes)
• Define develop and maintain customizations/integrations between various Kubernetes OSS tooling  (ingress helm operators observability)
• Perform application deployment of container applications to Kubernetes environments using CI/CD workflow tooling
• Manage AWS cloud infrastructure setup for services such as EC2 S3 EKS AWS Lambda API gateway etc
• Document common work tasks to be added to shared knowledge base
• Work closely with other business development teams to help them design and deploy their applications

Qualifications :

Required Qualifications:

• BS/MS in Computer Science Information Technology Computer Information Systems (or) equivalent working experience in IT field
• 10 years of experience in handling enterprise level infrastructure for storage memory network compute and virtualization using vSphere of VMWare
• Proven Experience in setting up continuous integration of source code pipelines using Bitbucket Jenkins Terraform Ansible and continuous deployment pipelines using Artifactory ArgoCD and Spinnaker
• Proven experience in and deep understanding of the Kubernetes architecture including the control plane and Kubernetes networking models including CNI (Container Network Interface) plugins (such as Calico & Flannel) Service Mesh architectures (Istio Linkerd) and Ingress Controllers. Expertise in resource allocation scaling using Pods finetune cluster performance configuring and managing persistent storage in Kubernetes. Strong focus on securing Kubernetes clusters including implementing best practices for secrets management (using tools like HashiCorp Vault)
• Proven Experience with endtoend Observability in Kubernetes environments using monitoring tools such as Prometheus Grafana and Logging solutions like Splunk.

• Strong understanding of network architecture and network virtualization including bandwidth management latency troubleshooting and capacity planning to ensure optimal data flow and resource allocation.
• Expertise in deploying and managing AWS services like EMR Redshift RDS and scaling AI and ML solutions on platforms like AWS Bedrock and Sagemaker.

• Candidate should be passionate about developing and delivering modern softwareasaservice (SaaS) design principles using Docker/Kubernetes
• Handson Python and Unix shell scripting is required with a strong advocate of DevOps principles.
• Strong troubleshooting skills with a strong appetite to learn new technology

Preferred Qualifications

• Certification in Kubernetes
• Proven Experience or Certification in one of major cloud providers such as AWS or GCP
• Deep Understanding of all AWS or GCP offerings for cloud computing and Gen AI solutions including Bedrock or VertexAI services
• Deep Understanding of services like EMR RDS (Aurora DB) Kafka and Redshift to support largescale data processing
• Understanding of MLOps tools for AI & Machine Learning such as Dataiku
• Deep Familiarity with data service solutions such as ElasticSearch Kafka Redis NiFi

Additional Information :

Because Western Digital thrives on the power of diversity and is committed to an inclusive environment where every individual can thrive through a sense of belonging respect and contribution we are committed to giving every qualified applicant and employee an equal opportunity.  Western Digital does not discriminate against any applicant or employee based on their protected class status and complies with all federal and state laws against discrimination harassment and retaliation as well as the laws and regulations set forth in the Equal Employment Opportunity is the Law poster.

Remote Work :

No

Employment Type :

Fulltime