Veeam · San Jose, CA, USA · по договорённости
Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands.
About the Role
We are seeking a Senior Software Engineer to join the Performance Engineering team for Data Connectors & High-Scale Ingestion. You will own the throughput, latency, scalability, and resource efficiency of multi-source ingestion pipelines that move data from SaaS, cloud, and on-premises sources into the platform at very large scale.
In this role, you will write performance tests, generate realistic datasets, build tooling that helps the team locate bottlenecks, and ship fixes and new features that improve the scalability of the product. You will also work customer-reported performance issues through to root cause and resolution.
What You’ll Do
Design and run performance and scalability tests for connectors and ingestion pipelines (throughput, latency, concurrency, soak), with dataset generators that reproduce realistic source data shapes, object counts, payload sizes, and change rates
Debug the full stack end to end (Go runtime, OS, network, datastores, Kubernetes, cloud) to root-cause bottlenecks and regressions such as goroutine leaks, lock and channel contention, GC pressure, connection pool exhaustion, TCP/TLS behavior, API rate limiting, and slow queries
Analyze production workloads and telemetry in Prometheus and Kibana to find bottlenecks, and build proofs of concept that become product improvements
Build tooling that speeds up bottleneck analysis, such as automated pprof and trace capture and run-to-run regression comparison
Fix performance issues and implement new features in product code, including parallelism and pipelining, batching, back-pressure handling, and connection and memory reuse
Tune PostgreSQL, Redis, and Databricks usage on the ingestion path, and optimize resource usage and autoscaling of ingestion workloads on Kubernetes across AWS and Azure
Own customer-reported performance issues through root cause and resolution, in partnership with Support and Engineering
Participate in design and code reviews so new features are performant by design, and document sizing guidance and best practices
What You’ll Bring
5+ years of experience developing enterprise solutions in a high-level programming language such as Go, C++, or Java
Experience with distributed systems concepts and client-server architectures
Expertise in developing, testing, and debugging production-quality, scalable, multi-threaded, and concurrent systems
Strong knowledge of computer science fundamentals (data structures, algorithms, and concurrency)
Hands-on experience with Kubernetes, AWS, and Azure, including diagnosing resource, scheduling, networking, and API-limit issues in running workloads
Bonus Skills
Experience building data connectors or ingestion pipelines (REST, gRPC, CDC, Kafka, or similar)
Experience profiling and tuning production services (CPU, memory, lock contention), including eBPF-based or continuous profiling tools
Experience with databases and/or storage systems, especially in the public cloud
What you'll get
Unlimited paid time off, 12 paid holidays including 4 global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares
Paid parental leave: 8 weeks for all parents, 16 weeks for birthing parents
Medical, dental, and vision coverage starting on your first day
Mental health support, therapy ses
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