Sam M.

About Sam M.

Senior Site Reliability & Platform Engineer with 7+ years of experience designing and operating secure, highly available cloud platforms across AWS, Azure, and GCP. I specialize in Zero Trust Architecture (ZTA), Kubernetes, and Infrastructure as Code, with deep expertise in supporting modern data platforms in FedRAMP-compliant environments.Currently at Axle Informatics, I architect mission-critical data infrastructure supporting NIH initiatives. My work focuses on platform reliability, cloud automation, and building clean-room analytics environments. I manage the full lifecycle of data movement ingestion, orchestration, and transformation ensuring systems are resilient, observable, and compliant with federal security standards.I bridge the gap between SRE principles and data platform engineering, enabling teams to run complex workloads with enterprise-grade reliability and Zero Trust security.Core strengths include: Security & Compliance: FedRAMP, Zero Trust Architecture (ZTA), IAM, PrivateLink, VPC Endpoints, NIST 800-53 Cloud & Platform Engineering: AWS, Azure, GCP | EKS, AKS, GKE | Secure VPC design, private networking Automation & IaC: Terraform, GitOps (ArgoCD), Python, Bash, CI/CD pipelines Container & Compute Platforms: Kubernetes, Docker, Helm, ECS, EMR Serverless Data Platforms (platform-focused): Dagster, Airbyte, Athena, Glue, Iceberg, Databricks, Collibra Observability: Prometheus, Grafana, CloudWatch, Azure Monitor, ELK, OpenLineage Reliability & SRE: SLIs/SLOs, incident response, MTTR reduction, operational excellence Databases: PostgreSQL, MySQL, MongoDB, DynamoDB, Redis, Cosmos DBHighlights:FedRAMP & NIH: Designed and operated high-availability platforms for large-scale NIH workloads in FedRAMP environments.Zero Trust: Implemented Zero Trust networking and secure data movement using VPC Endpoints and PrivateLink to protect sensitive research data.Secure Data Pipelines: Engineered hardened pipelines using Airbyte, Glue, Dagster, EMR Serverless, and Iceberg.Full-Stack Automation: Automated end-to-end deployments via Terraform, maintaining 100% IaC coverage.Operational Excellence: Improved observability and reduced MTTR through advanced monitoring and incident response strategies.What sets me apart is my ability to design platforms that are scalable, inherently secure, and compliant—specifically where infrastructure and data systems intersect.AWS Certified Solutions Architect | Microsoft Azure Certified | M.S. Computer Science

Experience

1. Sr Site Reliability Engineer

   AMH

   Apr 2025 — Present · Las Vegas, NV, US

   Architected resilient Kubernetes infrastructure on AKS for data platform workloads, implementing auto-scaling with Helm charts, self-healing pods, and achieving 99.99% uptime SLA for Databricks and Azure Data Factory pipelines• Built end-to-end GitOps workflow using GitHub Actions and ArgoCD, automating Docker container deployments across 3 environments with integrated quality gates, reducing deployment failures by 70%• Developed comprehensive Terraform modules for Azure data infrastructure (Databricks workspaces, ADF, Storage Accounts, VNets), enabling reproducible deployments and disaster recovery in <15 minutes• Implemented advanced observability platform using Azure Monitor, Prometheus, and Grafana, defining SLIs/SLOs and creating custom metrics that reduced MTTR from 45 to 12 minutes• Led 24/7 on-call rotation and incident management for critical data infrastructure, conducting RCAs, writing post-mortems, and implementing preventive measures that reduced P1 incidents by 65%• Drove FinOps initiatives optimizing infrastructure costs by 35% through implementing auto-scaling policies, spot instances for Databricks clusters, and automated resource cleanup using Python scripts• Automated network security configurations including VNet peering, Private Endpoints, and NSGs between Databricks, ADF, and on-premises systems, ensuring zero-trust network architecture• Integrated Collibra DQX rules into CI/CD pipelines as automated quality gates, using PySpark for data validation and preventing 85% of data quality issues from reaching production

Education

• San Francisco Bay University

  Masters, Computer Science

  2015 — 2016