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Sr. Big Data Engineer
Job Order #14747
San Francisco, California - Added Jul 12, 2018

Full Description:

• Expert-level Java development experience, including common backend frameworks.
• Hands-on development with key AWS technologies, including AWS Batch, AWS StepFunctions, and AWS Lambda.
• AWS Certified Developer or other AWS certification.
• Experience with highly-scalable and distributed databases and the key issues affecting their performance and reliability.
• Experience using high-throughput, message queueing systems such as AWS SQS.
• Familiarity with DevOps technologies, including Docker and common configuration management tools.
• An ability to periodically deploy systems to cloud environments such as AWS.
• Mastery of key development tools such as GIT, and familiarity with collaboration tools such as Jira and Confluence or similar tools.
• Overall, 7+ years of industry experience developing backend components with a recent focus on big data systems.
• Bachelor’s degree or equivalent required, Master’s degree preferred.

• Experience or understanding of developing machine/deep learning systems in a distributed environment.

Job Description:
• Sr. level, hands-on position; responsible for leading the design and development of cutting-edge big data systems to enable the company/R&D to better understand and serve their customers.
• Will engage in an international engineering collaboration with the teams developing global-scale infrastructure; supporting acquisition, analysis, and machine learning; using data coming from future product releases of the company.
• Products impacted by this role range from customer insights informing new services to the most advanced autonomous systems in the industry.
• Design and implement key components for highly scalable, distributed data collection and analysis system built for handling petabytes of data in the cloud.
• Analyze and support requirements from machine learning specialists, focusing on the most important topics in the rapidly evolving industry.
• Move architecture and implementation through the development pipeline, from research to deployment in millions of units.
• Work with architects from other divisions contributing to this analytics system and mentor team members on best practices in backend infrastructure and distributed computing topics.

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