Tango operates a live-streaming social app at significant scale, evidenced by a tech stack heavy in data infrastructure (BigQuery, Kafka, Airflow, Vertex AI) and ML frameworks (TensorFlow, PyTorch, scikit-learn). Active projects span mobile performance, video processing pipelines, and scalable data lakes—reflecting engineering priorities around handling high-volume user data and real-time analytics. The hiring mix skews senior (35 of 84 engineering/data roles) and engineering-focused (42 of 84 across eng+data), suggesting either rebuilding legacy systems or scaling distributed infrastructure for a platform at the 400M-download mark.
Notable leadership hires: Tech Lead
Tango is a social live-streaming app and creator platform with over 400 million downloads worldwide. The product centers on live content discovery, creator monetization (described as a "digital economy"), and user-to-user connection. The company operates regional offices in Kyiv, Limassol, Warsaw, Dubai, and Tel Aviv, with engineering and data teams distributed across Poland, Israel, Ukraine, and Cyprus. Current scaling priorities include mobile performance optimization, video processing pipelines, and real-time analytics infrastructure to support a growing user base and revenue model tied to creator payouts.
Tango's backend runs on Java/Spring with SQL/MySQL and PostgreSQL-compatible databases. Data infrastructure uses GCP (BigQuery, Vertex AI, GCS), Kafka for streaming, Redis for caching, and Apache Airflow for pipelines. Frontend is React SPA. ML relies on TensorFlow, PyTorch, and scikit-learn. Adopting Terraform for infrastructure.
Core projects include React SPA optimization for high-load apps, mobile performance tuning, video processing pipelines, scalable data lakes, real-time analytics infrastructure, feature flags, and lifecycle CRM campaigns. Also refactoring toward micro-frontends and implementing A/B testing frameworks.
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