Engineering Manager - Last Mile Platform

Job Purpose

Platform Architecture & Engineering Leadership

• Architect, build, and operate large-scale event-driven microservices in Java, Node.js, and Python platforms powered by Confluent Kafka for real-time order processing, delivery orchestration, and logistics intelligence.
• Lead the engineering strategy for last-mile delivery systems, handling millions of order transactions per month across multiple MENA markets.
• Drive platform scalability, resiliency, observability, and high availability, ensuring enterprise-grade SLAs and operational stability.
• Define and implement best practices for distributed systems, asynchronous messaging, API management, and event-driven integration patterns.
• Provide technical leadership for cloud-native application development using containerized and Kubernetes-based architectures.

Cloud & Data Infrastructure

• Design and manage Azure-native enterprise platforms leveraging:

• API Management (APIM)

• PostgreSQL

• Azure AI/ML Services

• Event-driven integration services
• Ensure platform reliability with a target uptime of 99.99% through proactive monitoring, disaster recovery planning, and performance optimization.
• Build scalable data pipelines and integrated data ecosystems enabling advanced analytics, AI/ML, and operational reporting.

Data Integration & Enterprise Analytics Enablement

• Lead integration initiatives across:
• Restaurant POS systems
• Delivery logistics platforms
• Customer mobile/web applications
• Financial and reporting systems
• Enterprise operational platforms
• Create unified operational data layers supporting:
• Delivery time prediction
• Logistics efficiency optimization
• Store performance analytics
• Customer behaviour analysis
• Workforce and capacity planning
• Partner with analytics and data science teams to ensure platform readiness for enterprise-scale data mining and predictive intelligence initiatives.

AI/ML & Intelligent Automation

• Lead deployment and operationalization of AI/ML models using Python-based ecosystems, including:
• Neural Prophet
• XGboost
• Scikit-learn
• TensorFlow
• Predictive analytics frameworks
• Enable intelligent operational capabilities such as:
• Dynamic order routing
• ETA prediction
• Delivery capacity optimization
• Demand forecasting
• Drive MLOps best practices, including model deployment, monitoring, retraining, and lifecycle governance.

Engineering Management & Stakeholder Collaboration

• Manage and mentor high-performing engineering teams, including backend engineers, DevOps engineers, architects, and data engineers.
• Collaborate with product management, operations, finance, and executive leadership to align technology initiatives with business objectives.
• Drive agile delivery execution, sprint planning, engineering governance, and release management.
• Own technical roadmap planning, architecture reviews, risk management, and vendor coordination.
• Establish engineering KPIs, operational metrics, and platform performance governance.

Required Qualifications

• Master’s degree in Computer Science, Engineering, Information Technology, or related field.
• 15+ years of experience in enterprise software engineering with at least 3+ years in engineering leadership or architecture management roles.
• Strong experience designing and operating event-driven architectures using Confluent Kafka or Apache Kafka ecosystems.
• Extensive experience with cloud-native technologies on Microsoft Azure.

Proven Expertise In

• AKS/Kubernetes
• Microservices architecture
• API-first integration
• Distributed systems
• Real-time data streaming
• Hands-on experience with PostgreSQL, Data Lakes, and enterprise integration architectures.
• Experience deploying and managing AI/ML solutions using Python frameworks such as TensorFlow and Scikit-learn.
• Strong understanding of CI/CD, DevSecOps, observability, and platform reliability engineering.
• Experience in logistics, QSR, e-commerce, supply chain, mobility, or last-mile delivery domains is highly preferred.