11 hours ago
Remote, United StatesStaff+
Responsibilities
- Design and develop multi-threaded asynchronous replication systems with parallel streaming capabilities.
- Build object-level delta replication with checkpointing and resume functionality.
- Develop bucket- and share-level replication controls and secure data transfer mechanisms using TLS 1.3 with mutual authentication.
- Implement checksum validation, metadata tracking, change detection, retry, failover, and recovery workflows.
- Build REST APIs for replication configuration, control, and automation.
- Develop replication status visibility, alerting, monitoring dashboards, and operational insights.
- Ensure high availability, fault tolerance, scalability, performance, and data integrity.
- Partner with QA and backend, security, and platform teams on performance, resiliency, scale validation, and end-to-end workflows.
- Debug production issues and improve replication reliability.
- Provide technical leadership, architectural guidance, and mentorship to the engineering team.
Requirements
- 8+ years of experience in distributed systems, storage systems, or backend software engineering.
- Strong programming skills in one or more of C++, Go, Java, or Rust.
- Experience designing and building data replication systems, data pipelines, or distributed data services.
- Deep understanding of distributed systems concepts including consistency, availability, scalability, and fault tolerance.
- Strong expertise in multi-threading, concurrency, and parallel processing.
- Knowledge of TCP/IP, HTTP/HTTPS, TLS, networking protocols, and secure communication.
- Experience implementing checksums, validation, and consistency checks for data integrity.
- Experience designing and building REST APIs and service-based architectures.
- Familiarity with checkpointing, failure recovery, retry mechanisms, metrics, logging, and alerting.
- Strong debugging, problem-solving, and system design skills.
- Preferred experience with asynchronous replication, disaster recovery, backup systems, object storage, large-scale storage systems, delta encoding, change data capture, incremental synchronization, and high-throughput data movement.
- Preferred exposure to mutual TLS, encryption, authentication, enterprise-scale data platforms, performance optimization, and large-scale system tuning.
About DDN
DDN builds high-performance data storage and data management systems for AI, machine learning, and high-performance computing workloads used by enterprises, research institutions, and governments. It sells appliance hardware and software (including parallel file systems and AI data platforms) along with support and professional services. Founded in 1998 and headquartered in Chatsworth, California, the privately held company reports serving over 11,000 organizations worldwide.