Ahmed Popal

Leading a team of 8+ senior developers, within the scope of a multi-million dollar, strategic project, so to deliver the company’s first attempt at providing mobility services for its user base of ~2M Designing & implementing resilient, self-healing and highly scalable applications (developed in Python), including: • RESTful interfaces (APIs), running as separate micro-services, communicating with others via message broker (saga/choreography pattern), providing support for synchronous & asynchronous operations in a secure, fail-safe, atomic and efficient manner • Orchestration-specific interfaces, adhering to the Asynchronous Request/Reply pattern, where several micro-services attempt to complete an end-to-end orchestration, each using processes that are capable of managing stateful transitions resiliently • Applications use Google Big Table for storage, Pub Sub & Cloud Task for messaging and event-driven loosely coupled requests, and Mermaid/OpenAPI for documentation Solution adheres to true CI/CD practices running on Cloud Build, with canary-based development support, feature-flagging, and versioning schemes built upon solid industry best-practice Designed and implemented monitoring, alerting (policy/incident-based approach), with support for end-to-end tracing of all business operations Solution follows best-practices in security & availability. VPCs/Shared VPCs in a Hub-Spoke pattern is adhered to for integrations with external teams, while availability is handled through GCP External Load Balancers (with Cloud Armor), attached to multiple backend pools To ensure the code quality, thoroughly tested all of the backend features using PyTest & PyTestBDD (unit testing and end-to-end), all while continuously emphasizing on code reviews, pull-requests and multiple quality-gates (e.g., SonarQube, White Source, etc.)

Proven ability to lead and manage a team of 10+ talented developers in the implementation of revenue-generating applications, resulting in $5 million in investment, government grants for R&D efforts, as well as in yearly revenue Implemented resilient, self-healing and highly scalable applications (developed in C#, and running on Azure Functions & Kubernetes), including, but not limited to: • A RESTful, GraphQL-enabled billing API that ensures secure, fail-safe, atomic and efficient transactions, built to adapt multiple payment systems • A RESTful, GraphQL-enabled recommendation API that sends customized marketing content dynamically • Both applications use CosmosDB & Azure Table Storage for storage, Event Grid & Service Bus for messaging and event-driven loosely coupled requests, and Mermaid/OpenAPI for documentation. They also make use of Azure Durable Functions for the orchestration of long-running tasks such as charging subscription fees ARCHITECTURAL DECISIONS To handle large traffic loads and failover when necessary, adopted technologies such as Azure Availability Zones, Azure Front Door, and Application Gateway, so to distribute traffic across multiple backend pools (globally distributed to only one region for now) Implemented proper monitoring and logging solutions within a cloud-based system using tools such as Azure Monitor Designed and implemented intrusion detection/prevention systems to protect against network threats (DDOS, Sql Injection, etc.), using technologies such as Azure Firewall, Azure Virtual Network; configured VNETs, VPN gateways, and subnets to segment and isolate resources within the cloud environment using the Hub/Spoke pattern Designed and implemented a big data infrastructure, utilizing technologies such as Stream Analytics, Event Hub, Data Lake, and Databricks to effectively store, transform, and serve data to customers through user-friendly dashboards

Implemented resilient, self-healing and highly scalable applications (developed in C#), including, but not limited to: • A fail-safe chat system that utilizes SignalR Triggers (serverless) for real-time communication with clients & Cosmos DB & Table Storage for storage and a RESTful API for conversation creation/fetching • A notification system that enables the efficient delivery of notifications for both web and mobile devices, using Azure Notification Hubs & SignalR In ensuring a scalable code-base that can accommodate the growing needs of the system, made use of cloud patterns such as the saga, queue-based load levening and compensating transaction patterns To ensure the quality and reliability of the code, thoroughly tested all of the backend features using MSTest, Azure Test Plan, and SpecFlow (unit testing and end-to-end). In addition, followed Microsoft’s recommended C# best-practices, adhered to trunk-based development, all while continuously emphasizing on code reviews, pull-requests and multiple quality-gates (e.g., Sonar Cloud, White Source, etc.) To ensure CI & CD, automated the entire process of software delivery using Azure DevOps (including the deployment of resources with Terraform) • Languages applied: C#, Python, PowerShell • Cloud-Specific Services: App Services, Application Gateway, Private VNets, Private Endpoints, Azure Kubernetes, , Keyvault, Azure Functions, Traffic Manager, Azure’s Active Directory & B2C, SQL Cloud, Azure Cosmos DB, Azure Redis Cache, Databricks Clusters, Event Hub, Stream Analytics and Data Factory.