Klaviyo is growing fast and we have openings for all skill levels across all of our teams. Learn more about our engineering culture at https://klaviyo.tech We love tackling tough engineering problems and look for Engineers who are passionate about building, owning, and scaling features and breaking through any obstacle or technical challenge in their way. We push each other to move out of our comfort zone, learn new technologies and work hard to ensure each day is better than the last.
Klaviyo operates a real-time data platform written in Python and built for massive scale on Amazon Web Services (AWS). Engineers come to Klaviyo with experience in a variety of languages and from a number of disciplines.
Team Overview The Data Warehousing Team is responsible for the majority of real-time analytical queries at Klaviyo. We process thousands of queries per second to power Klaviyo's analytical reporting capabilities.
Responsibilities As a senior engineer on this team, you will be responsible for designing, building, and maintaining systems to support core product areas in Klaviyo. You will work with a cross functional team to help refine feature specifications, write technical design documents, create system infrastructure, write high quality code, and operate large scale systems in production. You will also review other engineer's designs and code to provide technical feedback and improvements as you grow your own skill set.
Team Tech Stack Python
ClickHouse
Kafka
ZooKeeper
Django
Redis
Required Skills Highly skilled in using at least one modern programming language 5+ years of experience in a software engineering discipline Significant experience with backend, service oriented application development Experience with OLAP databases schema design normalization / denormalization trade-offs performance operations Able to communicate well Able to work with others on a team Able to learn continuously and adapt to a high growth environment Able to stick with and solve difficult problems Preferred Skills Experience with OLTP databases schema design normalization / denormalization trade-offs performance operations Experience with distributed systems Experience performance tuning and scaling systems Experience with high volume data processing and storage systems Experience using Linux operating systems
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