Wayfair.com is a leader in the e-commerce space for all things home. The Distributed Computing team is looking for smart, passionate and curious people who are excited to help us scale, support and engineering our distributed analytic and streaming infrastructure. With the broad reach of the technologies we are using you will have the opportunity to grow your network and skills by being exposed to new people and ideas who work on a diverse set of cutting-edge technologies. If you are the type of person who is fascinated by engineering extremely large and diverse unstructured data sets and if you are passionate about troubleshooting challenging technical problems that in-memory or on-disk batch processing bring along, we should talk. Tasks Consult with our internal customers on their requirements, document, share updates and solve any production issues Analyze a request to determine, recommend, and plan installation of a new system or modification of an existing system Use configuration tools such as Puppet, Salt, Pepper, etc for configuring BigData and Messaging systems like Hadoop, Kafka, Rabbit, etc Build specs, system test plans and get them approved by stakeholders Coordinate installation of our systems with our stakeholders across the company Build, install, upgrade or migrate petabyte size big data systems Update Project Tracker with time spent on each project and update the status Confer with our data scientists and other clickstream developers to obtain information on limitations or capabilities for data processing projects Monitor functioning of our big data and messaging systems to ensure they operate at their peak performance at all times Mentor the junior members on the team Advise internal customers/stakeholders about or perform maintenance of our systems Optimize and tune Hive and spark queries using data layout techniques such as partitioning, bucketing or other advanced techniques Drive best practices around big data and messaging systems usage Troubleshoot and root cause issues in our complex multi-tiered production system Technology Skills Bachelor's in Computer Science, Computer Engineering, or related field required Big Data: Hadoop (Cloudera or Hortonworks distribution) Messaging: Kafka or RabbitMQ Streaming and Batch Processing Platforms: Spark, Storm Configuration Management: Puppet, Salt, Ansible Operating Systems: Linux and Windows Skills & Abilities Excellent interpersonal and team building skills An analytical, creative, and innovative approach to solving problems An interest in working hard and being challenged in a fast-paced environment, and having fun while doing it About Us: Wayfair is one of the world's largest online destinations for the home. Whether you work in our global headquarters in Boston or Berlin, or in our warehouses or offices throughout the world, we're reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you're looking for rapid growth, constant learning, and dynamic challenges, then you'll find that amazing career opportunities are knocking. No matter who you are, Wayfair is a place you can call home. We're a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair - and world - for all. Every voice, every perspective matters. That's why we're proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or genetic information.
Associated topics: data analyst, data analytic, data center, data integrity, data quality, data scientist, data warehouse, data warehousing, database, mongo database administrator
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