Data Lake & Data Warehouse InfrastructureSupport the architecture and operations of infrastructure supporting enterprise-scale data lakes and cloud data warehouses (Redshift, Snowflake)Automate ingestion, transformation, and lifecycle policies using IaC and orchestration toolsSupport big data frameworksEnsure compliance, encryption, retention, and access control are enforced across all platformsMulti-Cloud Infrastructure & AutomationDesign modular, reusable infrastructure-as-code across AWS and AzureIntegrate security, cost optimization, DR, and compliance as code into platform blueprintsBuild GitOps-based deployment pipelines for infrastructure, ML services, and platform updatesImplement policy-as-code for environment governanceCybersecuritySecure cloud infrastructure across AWS, Azure & GCP, embedding defense-in-depth and zero-trust principles throughout network and compute layersImplement secure networking architectures including private connectivity, encryption in transit, and segmentation of critical workloadsHarden CI/CD pipelines with automated vulnerability scanning, secret management, and signed artifact verificationCollaborate with Security Operations to ensure cloud telemetry, threat detection, and incident response are integrated into platform monitoringCI/CD, Monitoring & ObservabilityBuild and manage scalable CI/CD pipelines supporting data, ML, and app workloadsIntegrate security scanning, test automation, and artifact promotionDeploy observability tooling across ML and data pipelinesEnable intelligent alerting and logging for infrastructure, pipelines, and AI servicesCross-Functional Collaboration & StrategyWork with data engineers, ML scientists, software teams, and security to deliver cohesive platformsShape strategy and future-state architecture for AI enablement and MLOpsMentor engineers on DevOps, Cloud Operations, IaC, cloud-native platforms, and data/ML workflowsContinuously improve automation maturity, developer velocity, and platform resiliencyYour Qualifications:8+ years in DevOps, cloud platform engineering, or SRE roles in enterprise environmentsProven experience with AWS and Azure for data platforms, ML infrastructure, and DevOps automationHands-on with SageMaker, Azure ML, Kubeflow, MLflow or other enterprise-grade MLOps platformsIaC expertise with Terraform or ARM/Bicep is a plusFluent in Python and/or Bash for scripting, automation, and platform integrationsExperience building and operating data lakes and data warehouses in the cloud (e.g., S3/ADLS, Redshift, Snowflake)Strong skills in CI/CD pipelines and DevSecOps practicesExperienced with monitoring and logging systemsUnderstanding of security, compliance, encryption, IAM, and policy-as-code in a cloud environmentExcellent collaboration and mentoring capabilities; strong communication across technical and business stakeholdersYour Career @ Brookfield Properties:At Brookfield Properties, your career progression is important to us. Role & Responsibilities:AI & ML Platform EngineeringDesign and build scalable cloud-native infrastructure for AI/ML platformsAutomate deployment of infrastructure as code and identify and execute on other areas for automation within cloud solutionsImplement end-to-end pipelinesCollaborate with ML teams to tune infrastructure for performance, reproducibility, and cost-efficiency.