Platform Ops Architect – Data Science Platform

DXC Technology • Plano, TX

2d • Hybrid

About The Position

DXC Technology (NYSE: DXC) helps global companies run their mission-critical systems and operations while modernizing IT, optimizing data architectures, and ensuring security and scalability across public, private, and hybrid clouds. The world’s largest companies and public sector organizations trust DXC to deploy services across the Enterprise Technology Stack to drive new performance levels, competitiveness, and customer experience. Learn more about how we deliver excellence for our customers and colleagues at DXC.com. The candidate must be highly hands-on with Databricks on AWS, comfortable with Terraform-based infrastructure provisioning, and able to improve DevOps/MLOps processes across Dev, QA, and Production environments. The person must also be comfortable working in ambiguity and bringing structure to evolving platform needs.

Requirements

• 7–10 years of experience in platform operations, cloud engineering, DevOps, MLOps, or data platform support.
• Strong hands-on experience with Databricks on AWS.
• Strong hands-on experience with Terraform for infrastructure provisioning.
• Good understanding of AWS services such as IAM, S3, VPC, EC2, CloudWatch, KMS, Secrets Manager, Lambda/Glue.
• Experience managing Dev, QA, Stage, and Production environments.
• Strong understanding of CI/CD, release management, deployment automation, rollback, and production support.
• Good understanding of MLOps concepts such as ML pipelines, model registry, model promotion, and production monitoring.
• Strong troubleshooting, documentation, communication, and stakeholder management skills.
• Must be able to work independently in ambiguous and changing environments.

Nice To Haves

• Databricks Asset Bundles, Databricks CLI, dbx, or similar deployment tools.
• Airflow, AWS Step Functions, or Databricks Workflows.
• Unity Catalog governance, data quality, lineage, and access-control experience.
• Observability tools such as CloudWatch, Splunk, Datadog, Grafana, or Prometheus.
• Docker, Kubernetes, or EKS.
• AWS SageMaker, Bedrock, GenAI, RAG, vector search, or LLM workload experience.
• Databricks/AWS cost optimization and FinOps exposure.

Responsibilities

• Maintain, enhance, and support the enterprise Data Science Platform.
• Provision and manage platform environments for multiple teams using Terraform and AWS.
• Support deployment and productionization of ML pipelines, data pipelines, notebooks, jobs, workflows, and platform features.
• Standardize promotion of changes from Dev → QA → Prod.
• Work hands-on with Databricks workspaces, clusters, jobs, workflows, Unity Catalog, Delta Lake, MLflow, secrets, access controls, and deployment patterns.
• Improve platform reliability, security, performance, cost, monitoring, and operational efficiency.
• Create reusable automation, Terraform modules, runbooks, release processes, and operating standards.
• Troubleshoot platform, Databricks, AWS, CI/CD, access, pipeline, and deployment issues.
• Work with data science, data engineering, DevOps, cloud, security, and product teams.

Benefits

• In-person collaboration
• Flexibility to support wellbeing, productivity, individual work styles, and life circumstances
• Inclusive environment where everyone can thrive

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed