Software Engineer, Distributed Systems (Core)
New
T
True Talent Solutions PartnersData activation platform
Fully remote within the United States.Full-TimeStaff
Salary$180,000 to $320,000 USD annually, plus equity.
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Job Details
- Experience
- 5 or more years
- Required Skills
- DockerSQLKafkaKubernetesSparkDistributed Systems
Requirements
- 5 or more years of backend engineering experience building and scaling distributed systems at high-growth companies (Series A through Series E stage).
- Staff-level or equivalent seniority, with a track record of rapid progression and meaningful recent tenure at growth-stage companies.
- Deep expertise in distributed systems design: how large-scale systems behave under load, failure modes, and how to architect for the next order of magnitude.
- Hands-on experience building event collection or data streaming services using tools such as Kafka, message queues, SQL databases, Kubernetes, and Docker.
- Experience owning systems through multiple orders of magnitude of growth and driving the architectural changes required.
- Familiarity with how infrastructure-layer tools (Spark, Flink, Kafka, and similar) are built, not just used.
- Strong product thinking and comfort engaging with product specifications alongside technical work.
- Excellent communication skills and a collaborative approach to technical problem-solving.
- Strong computer science fundamentals, ideally from a rigorous academic background.
Responsibilities
- Design and optimize the syncing engine to move data faster to destinations like ad platforms, squeezing performance across every stage of the pipeline.
- Architect and build real-time and streaming sync capabilities on top of existing batch infrastructure, including support for webhook and queue-based sources.
- Identify and resolve scalability and reliability bottlenecks as the platform grows by orders of magnitude.
- Maintain and extend a low-latency caching layer (sub-30ms p90, millions of QPS) that powers real-time personalization use cases on top of data warehouses.
- Expand multi-region and multi-cloud infrastructure to support data residency requirements for a global customer base.
- Collaborate directly with customers to diagnose and solve their hardest scaling challenges.
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