Big Data DevOps Engineer

Singapore

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Posted 2 weeks ago

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?

Responsibilities

  • Ensure performance and availability of big data infrastructure
  • Deploy and operate big data components according to business scenarios
  • Response to incidents promptly and identify potential issues
  • Keep learning big data technologies and continuously optimize performance, availability and scalability

Qualifications

  • 3+ years of Big Data DevOps experience
  • Familiar with data pipeline including batch ETL, realtime streaming and job scheduling
  • Hands on experience on big data components including Hadoop, Hive, Spark, Spark Streaming, Presto, HBase, Elasticsearch, Kafka, ZooKeeper, Redis, Airflow
  • Experienced in deploying, operating, monitoring, optimizing and troubleshooting large scale big data infrastructure
  • Proficient in shell scripting, Python and SQL
  • Experiences with AWS big data services is a plus
  • Team working, analytical mind, be optimistic, willing to accept challenges and quick response against incidents
  • Due to business nature and smooth collaboration within teams, bilingual is a must - English and Mandarin
Conditions• Do something meaningful; Be a part of the future of finance technology and the no.1 company in the industry• Fast moving, challenging and unique business problems• International work environment and flat organisation• Great career development opportunities in a growing company• Possibility for relocation and international transfers mid-career• Competitive salary• Flexible working hours, Casual work attire
Job tags: Airflow AWS Big Data Crypto ETL Finance Hadoop Kafka Python Spark SQL
Job region(s): Asia/Pacific Remote/Anywhere
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