Founded by Changpeng Zhao (CZ) in 2017, Binance is currently the largest cryptocurrency exchange in terms of daily volume. Binance is the core global exchange. However, Binance operates separate exchanges in some countries such as the US, UK, Singapore, and Turkey due to regulatory reasons.
Since Binance has global operations, the exchange does a lot of hiring on a regular basis. Being a market leader, Binance Jobs also come with significant perks. Most of the jobs are remote, with flexible working hours. Binance also offers health insurance, the option to be paid in crypto, and programs to develop your skills.
If you're looking for Binance US Jobs, a wide range of them are also available most of the time. On average, the Binance Interview process lasts 2-4 weeks with 4 steps: Application Review, Interview, Offer, and finally Onboarding.
Binance is the global blockchain company behind the world’s largest digital asset exchange by trading volume and users, serving a greater mission to accelerate cryptocurrency adoption and increase the freedom of money.Are you looking to be a part of the most influential company in the blockchain industry and contribute to the crypto-currency revolution that is changing the world?
Job Responsibilities
- Develop and maintain data engineering systems across the data lifecycle, including data pipelines for batch and streaming applications, data storage layer and data processing engines
- Develop APIs to support high throughput data processing, feature engineering, risk algorithms and data science use cases.
- Develop data quality monitoring and alert systems to ensure high availability and high quality data sources.
- Design and upgrade data architecture to support new data applications, technical enhancements and business requirements.
Job Requirements
- Only fresh graduates or candidates with 1-3 years of experience need apply.
- Understand in Java language, Spring framework, and micro-service architecture.
- Proficient in big data pipeline development including batch and streaming processing.
- Understanding with big data components (e.g. Hadoop, Hive, Spark, Spark streaming, Flink, Presto, Hbase, Kafka, Zookeeper, Airflow, Elasticsearch, Redis).
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