• Design, construct, install, test and maintain highly scalable data pipelines with state-of-the-art monitoring and logging practices.

• Investigate and resolve performance and stability issues in data processing systems and advise necessary infrastructure changes
• Select and integrate data tools and frameworks required to provide requested capabilities
• Recommend ways to improve data reliability, efficiency and quality.
• Collaborate with Data Scientists, DevOps and Project Managers on meeting project goals.

Minimum qualifications:
• BS or MS in Computer Science or Computer Engineering
• Proficient understanding of distributed computing principles
• Data warehouse experience with major ETL tool. The experience and knowledge of good hands in any ETL tools is required.
• Familiar with relational database and NoSQL database. like MySQL, Hadoop/HBase, MongoDB, Redis…etc
• 3+ years of experience in working with big data using technologies like Spark, Kafka, Flink, Hadoop, and NoSQL datastores.
• 2+ years of experience on distributed, high throughput and low latency architecture.
• 2+ years of experience deploying or managing data pipelines for supporting data-science-driven decisioning at scale.

Preferred qualifications:
• A successful track-record of processing and extracting value from large disconnected datasets.
• Machine learning or statistics related knowledge
• Experience with the AWS ecosystem tools and system level DevOps tools