Senior Software Engineer – Reconciliation & Data Platform

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users. We are trusted by 300+ million people in 100+ countries for our industry-leading security, user fund transparency, trading engine speed, deep liquidity, and an unmatched portfolio of digital-asset products. Binance offerings range from trading and finance to education, research, payments, institutional services, Web3 features, and more. We leverage the power of digital assets and blockchain to build an inclusive financial ecosystem to advance the freedom of money and improve financial access for people around the world.

Responsibilities: Design and implement reconciliation frameworks to detect discrepancies across financial systems (trading, settlement, commission, etc.) Build and maintain real-time and batch data pipelines using Apache Flink and Hive Write complex SQL for data validation, anomaly detection, and root-cause analysis Collaborate with Finance, Risk, and Product teams to define reconciliation rules and SLAs Optimize system performance and reliability for high-volume, low-latency reconciliation scenarios Leverage AI/LLM tooling to accelerate development, automate anomaly triage, and improve operational efficiency

Requirements: 3+ years of backend development experience, primarily in Java Strong SQL skills — able to write and optimize complex queries for large datasets Hands-on experience with big data frameworks: Apache Flink (streaming) and Hive (batch/warehouse) Data-sensitive mindset: comfortable reasoning about data accuracy, consistency, and edge cases Experience in financial reconciliation, settlement systems, or data quality engineering is a strong plus Familiarity with AI tools (Copilot, LLM-based automation, etc.) and ability to apply them in daily engineering work is a plus

Nice to have: Experience with data warehousing concepts (partitioning, slowly changing dimensions, data lineage) Familiarity with Kafka, Spark, or similar data infrastructure Background in crypto, fintech, or high-frequency trading environments