Cloud & AI Infrastructure Engineering Leader | Over 10 years experience architecting secure, scalable systems across enterprise, federal, and high-performance environments.

Leading globally distributed engineering teams (US, India, Philippines) building everything from multi-region Azure hub-spoke architectures to GPU/HPC clusters and GenAI-driven data pipelines. My career spans carrier-grade networking, enterprise cloud, DoD-cleared environments, and AI infrastructure — always at the intersection of complex systems and automation.

• GenAI & Data Engineering — Building end-to-end data pipelines on Microsoft Fabric (OneLake, Data Factory, Data Warehouse, Data Science) with Snowflake integrations and FastAPI-based microservices for real-time data access
• GPU/HPC Infrastructure — Multi-tenant GPU cluster design with RDMA/RoCEv2 optimization, Kubernetes GPU scheduling, and observability via Prometheus + custom ROCm exporters
• Cloud Architecture at Scale — Multi-region Azure hub-spoke topologies with ExpressRoute, CheckPoint NVAs, BGP peering, and Terraform IaC for Fortune 100 clients
• AI-Driven Automation — LLM-powered infrastructure validation, configuration generation, and intelligent data quality monitoring using Python and prompt engineering

ISP / Telco Network Engineering     →  MPLS, BGP, voice architecture, carrier-grade data transport
Enterprise Cloud & DevOps           →  IaC, CI/CD, Kubernetes, hybrid cloud migrations (100+ sites)
Federal / DoD Cloud Engineering     →  Azure Gov IL4/IL5, DoD Cloud SRG, DISA STIGs, NIST 800-53
AI Infrastructure & Data Platforms  →  GPU clusters, Microsoft Fabric, Snowflake, GenAI pipelines

Designed enterprise hub-spoke topology across multiple Azure regions with ExpressRoute peering, CheckPoint NVA security, and automated failover. Led 15+ engineers across 4 countries.

Engineered resilient emergency communications infrastructure across classified network boundaries with real-time failover between naval vessels and shore command.

Translated NIST 800-53 controls and DISA STIG requirements into actionable Azure Government IL4/IL5 deployment patterns with automated compliance validation via FastAPI reporting services.

Built Python-based LLM pipeline for automated data validation, anomaly detection, and self-healing data quality workflows across Azure Data Factory pipelines.

Orchestrated end-to-end analytics on Fabric — OneLake ingestion, Data Factory workflows, Fabric Data Warehouse transformations, Data Science workloads, and Power BI dashboards with Snowflake connectors.

Custom observability pipeline for multi-tenant GPU clusters using Prometheus, Grafana, Loki, Alloy, and ROCm-SMI exporters with Kubernetes-native telemetry collection.

Languages & Frameworks: Python, FastAPI, Flask, SQL, Bash, PowerShell, Go (limited), Jinja2

Data & AI Platforms: Microsoft Fabric (OneLake, Data Factory, Data Warehouse, Data Science, Power BI), Snowflake, Azure Data Lake, GenAI/LLM integration, MLflow, DVC

Cloud & Infrastructure: Azure (Expert), AWS, GCP, Terraform, Kubernetes, Docker, Helm, Argo CD, Cluster API, Talos Linux, GitHub Actions

Networking: BGP, OSPF, ExpressRoute, MPLS, SD-WAN, VXLAN, RDMA/RoCEv2, Istio, GPU/HPC fabrics

Observability: Grafana, Prometheus, Loki, Alloy, OpenTelemetry, ROCm-SMI, Azure Monitor, CloudWatch

Security & Compliance: DoD Cloud SRG, DISA STIGs, NIST 800-53, Zero Trust, IAM/RBAC, OPA Gatekeeper, Trivy, HashiCorp Vault

• Azure Solutions Architect Expert
• Azure Network Engineer Associate
• Azure Data Engineer Associate (in progress)
• Microsoft Fabric Analytics Engineer
• AWS Cloud Practitioner
• CompTIA Security+
• JNCIA

Technical blogs and case studies on Medium: medium.com/@bookfan2200

💼 linkedin.com/in/danabindra ✍️ medium.com/@bookfan2200

Nonprofit in progress: hustlestack.ai