Dmitry – AWS, Python, Kubernetes

The platform enables the collection, storage, and processing of vast amounts of educational data from diverse sources, such as student interactions, assessments, and content usage. Leveraging AI and advanced analytics, it delivers personalized learning paths, real-time feedback, and predictive insights to educators and learners. The project aims to build a scalable, secure, and highly available cloud infrastructure to support large-scale data processing, machine learning workflows, and personalized education experiences.

Dmitry works as a Cloud Engineer specializing in designing and managing big data platforms that power EdTech and AI-driven learning solutions.

• Architects, designs, and develops large-scale data platforms and data applications;
• Deploys and maintains large-scale multi-tier cloud applications and environments;
• Works with Big Data services on Google Cloud Platform services (e.g. Big Query, Google Analytics) and AWS (e.g. EC2, S3, Athena, Lambda, Redshift, EKS, Open Search). Helps teams scale big data platforms and manage Data infrastructure, Data monitoring, Data lifecycle.

An internal platform for various client infra needs. The platform provided a robust foundation for application deployment using AWS services. It automated infrastructure provisioning, configuration, and CI/CD pipelines, ensuring high availability, security, and scalability. This enabled development teams to focus on delivering features without worrying about underlying infrastructure complexities.

Who it was for: The product was targeted primarily at enterprise customers who were migrating legacy workloads to AWS or building new cloud-native applications/microservices. These clients needed reliable, repeatable, and secure cloud infrastructure to accelerate their software delivery and reduce operational overhead.

• Acted as the technical delivery lead for projects involving complex network architectures, hybrid cloud integrations, and advanced connectivity solutions across AWS, Azure, and client data centers;
• Designed and deployed transitive networking architectures leveraging AWS Transit Gateway, VPC peering, hybrid connectivity (Direct Connect and ExpressRoute), and multi-region redundancy to support high availability and scalability. Worked on integrating production-grade Palo Alto firewall solution for the enterprise customer in AWS;
• Architected and implemented secure VPN solutions, including Site-to-Site VPNs for DCs and Azure, client VPNs with AWS, OpenVPN, and Wireguard;
• Engineered low-latency VoIP solutions by utilizing AWS Local Zones and direct network peering. Designed and assisted in building a low latency cloud-based solution for a latency-sensitive client using a combination of AWS EKS, kamailio with freeswitch;
• Developed Infrastructure-as-Code (IaC) solutions using Terraform and AWS CloudFormation to automate the deployment of networking components such as VPCs, subnets, NAT gateways, and Route 53 configurations. Integrated network automation with CI/CD pipelines for rapid iteration and delivery;
• Implemented robust network monitoring and logging solutions using AWS CloudWatch, VPC Flow Logs, Datadog, and custom-built dashboards. Designed security postures with AWS Network Firewall, WAFs, Security Groups, NACLs, and third-party intrusion detection systems (IDS);
• Assisted clients in migrating workloads to cloud environments by designing scalable and secure network topologies. Optimized traffic flows using ALB, NLB, and Global Accelerator to enhance application performance and reduce latency;
• Contributed to designing a private/public hybrid DNS solution to meet industry standards and project requirements.

This is the biggest consumer electronics retailer in North America. A platform for selling electronics and a variety of related merchandise in Canada.

As a Cloud Engineer, Dmitry led the deployment and management of big data platforms on AWS and Azure, ensuring high availability and performance. He specialized in OpenShift-based DevOps and DevSecOps pipelines—building CI/CD workflows that integrated security scanning, automated testing, and compliance checks seamlessly into the software delivery process.

• Architected and maintained Azure-based infrastructure with SRE best practices—monitoring, incident response, and capacity planning;
• Managed and optimized OpenShift clusters for containerized application deployment and scalability;
• Developed Infrastructure as Code (IaC) with Terraform and Azure ARM templates to automate environment provisioning;
• Implemented DevSecOps controls using tools like Aqua Security, Trivy, and GitHub Actions to enforce security at every stage;
• Drove cross-team collaboration to improved deployment frequency, reducing failures, and accelerating recovery times.