eMAG is a 6,000-person e-commerce operator across Romania, Bulgaria, Poland, and Hungary, built on AWS infrastructure with Kafka-backed event streaming, TensorFlow/PyTorch for recommendations, and heavy CRM tooling (HubSpot, Salesforce, Braze). Hiring velocity is accelerating with a 5:1 sales-to-engineering ratio, and active projects cluster around seller program scaling (lead generation, onboarding, visibility) and logistics optimization—suggesting the business is shifting from pure consumer retail toward a multi-vendor marketplace model with infrastructure strain.
eMAG operates a multi-country e-commerce platform in Romania, Bulgaria, Poland, and Hungary, serving both direct sales and third-party seller channels. The company employs over 6,000 people across four cities and operates regional warehousing and fulfillment operations. The tech stack reflects a maturing enterprise: cloud-native infrastructure on AWS, event-driven architecture via Kafka, ML-based personalization (TensorFlow/PyTorch), and business intelligence via Tableau/Power BI. Current operational focus spans seller program expansion, warehouse and transport flow optimization, and business planning model redesign—indicating scaling pressure across marketplace operations and logistics.
eMAG runs on AWS with VPC, Lambda, ECS, Kinesis, Athena, and API Gateway. The company is actively adopting AWS VPN, signaling enhanced infrastructure security and multi-region connectivity.
eMAG uses Kafka for event streaming, MySQL and SQL for transactional data, Redis for caching, Tableau and Power BI for analytics, and AWS Athena for query. TensorFlow and PyTorch support product recommendation and personalization features.
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