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Optimize the end-to-end data synchronization pipeline and build systems for real-time and streaming data, low-latency caching, and large-scale customer data movement. Identify and resolve scaling and reliability bottlenecks, operate multi-region and multi-cloud infrastructure, and own projects from design through delivery while working with customers on complex scaling challenges.
Join the core engineering team building and scaling distributed systems for a data activation platform. You will improve the systems that move large volumes of customer data, working across performance, reliability, and multi-region infrastructure.
Analyze and optimize the end-to-end syncing pipeline to move customer data more quickly.
Design systems that support real-time and streaming data sources, including webhooks and queues.
Identify scaling and reliability bottlenecks, then architect solutions for significant growth.
Build and improve low-latency caching services for real-time personalization use cases.
Develop and operate multi-region, multi-cloud infrastructure, including support for data residency needs.
Own projects from design through delivery and work directly with customers on complex scaling challenges.
At least 7 years of software engineering experience, with deep hands-on expertise in distributed systems and backend engineering.
Experience building complex, business-critical backend systems and scaling them through substantial growth.
Background creating event collection or data streaming services, and experience with message queues, Kafka, SQL databases, Kubernetes, and Docker.
Strong systems design fundamentals and familiarity with infrastructure-level technologies such as Spark, Flink, or Kafka.
Experience building scalable data sync systems that process and move large data volumes is valuable.
Strong communication skills, sound technical judgment, and an ability to learn quickly.
Base salary range: $180,000 to $320,000 annually. Visa sponsorship is available.
Remote, United States.
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