Cloud Data Platform Engineer

Role: Cloud Data Platform Engineer
Location: Remote
Duration: 12 months contract

Job Description:
The Cloud Data Platform Engineer will support and scale cloud-based data science and ML platforms. This role focuses on cloud infrastructure, DevOps automation, security, and platform reliability. You'll work closely with Data Science, ML, Data Engineering, and Platform Engineering teams to deliver secure, scalable, and reusable cloud patterns for analytics and ML workloads.

Core Responsibilities
Cloud Infrastructure & Platform Operations

• Manage, scale, and optimize cloud environments for data science and ML workloads
• Provision and operate compute platforms (EKS/Kubernetes, ECS, Databricks, SageMaker)
• Ensure high availability and performance for analytics platforms

DevOps, Automation & Reliability

• Build and maintain CI/CD pipelines for infrastructure, ML models, and platform services
• Implement monitoring, logging, and alerting (Datadog, CloudWatch, Prometheus, Grafana, ELK)
• Automate infrastructure using IaC tools (Terraform, CloudFormation) and GitHub Actions

Data Platform Enablement

• Enable data ingestion, transformation, and model execution workflows
• Build self-service tooling for data scientists (reproducible, scalable environments)
• Collaborate with Data Engineering on pipeline and platform integrations
• Support networking components (API Gateways, ALBs, CDNs, TLS, WAFs)

Security, Compliance & Governance

• Implement cloud security controls aligned with enterprise standards
• Support secure handling of sensitive financial data
• Conduct security reviews, risk assessments, and remediation

Cross-Functional Collaboration

• Act as a technical advisor for cloud architecture and ML production readiness
• Champion DevOps, Agile, and Platform Engineering practices
• Focus on internal developer experience, automation, and self-service

Required Skills & Experience

• 5+ years in Cloud Engineering, DevOps, Platform Engineering, SRE, or similar
• Strong AWS experience
• Hands-on Infrastructure as Code (Terraform, CloudFormation)
• Strong scripting skills (Python, Bash, or PowerShell)
• CI/CD experience (GitHub Actions, Jenkins, GitLab CI, ArgoCD)
• Container orchestration (Docker, Kubernetes/EKS, ECS)
• Experience supporting data-intensive or ML workloads
• Bachelor's degree or higher in a STEM field
• IAM, RBAC/ABAC, OAuth2, OIDC
• Secrets management and privileged access controls

Preferred / Nice to Have

• Financial services or other regulated industry experience
• Databricks, SageMaker, MLflow, Airflow
• AI/LLMOps experience (LLM observability, eval pipelines, agent workflows)
• Strong cloud networking knowledge (VPCs, security groups, routing)
• Distributed compute frameworks (Spark, Ray, Dask)