Staff Replication Development Engineer

    Highlights

    This role focuses on building enterprise-grade asynchronous replication capabilities that enable reliable and secure disaster recovery for large-scale data systems. DDN is seeking a Staff Replication Development Engineer to lead the design and development of the replication engine for the Infinia AI Data Platform.

    Numbers & Facts

    LocationNC

    Description

    DDN is seeking a Staff Replication Development Engineer to lead the design and development of the replication engine for the Infinia AI Data Platform. This role focuses on building enterprise-grade asynchronous replication capabilities that enable reliable and secure disaster recovery for large-scale data systems.

    You will work on developing high-performance replication pipelines, efficient data synchronization mechanisms, and secure data transfer systems. This role requires deep expertise in distributed systems and strong technical leadership to deliver a scalable and resilient replication foundation.

    Key Responsibilities

    • Design and develop multi-threaded asynchronous replication systems with parallel streaming capabilities

    • Build object-level delta replication with checkpointing and resume functionality

    • Develop replication engines supporting bucket/share-level replication controls

    • Implement secure data transfer mechanisms using TLS 1.3 with mutual authentication

    • Ensure end-to-end data integrity through checksum validation and verification pipelines

    • Design and implement manual failover workflows for disaster recovery scenarios

    • Build and maintain REST APIs for replication configuration, control, and automation

    • Develop metadata tracking and change detection systems to enable efficient replication

    • Implement RPO visibility, alerting, and operational insights for replication status

    • Contribute to monitoring dashboards focused on replication health and performance

    • Ensure systems are designed for high availability, fault tolerance, and scalability

    • Partner with QA teams to drive performance, resiliency, and scale validation

    • Collaborate with backend, security, and platform teams to deliver end-to-end replication workflows

    • Participate in debugging, production issue resolution, and continuous improvement of replication reliability

    • Provide technical leadership, architectural guidance, and mentorship to the engineering team

    Required Qualifications

    • 8+ years of experience in distributed systems, storage systems, or backend software engineering

    • Strong programming skills in one or more languages: C++, Go, Java, or Rust

    • Experience designing and building data replication systems, data pipelines, or distributed data services

    • Deep understanding of distributed systems concepts (consistency, availability, scalability, fault tolerance)

    • Strong expertise in multi-threading, concurrency, and parallel processing

    • Knowledge of networking protocols and secure communication (TCP/IP, HTTP/HTTPS, TLS)

    • Experience implementing data integrity mechanisms (checksums, validation, consistency checks)

    • Experience designing and building REST APIs and service-based architectures

    • Familiarity with checkpointing, failure recovery, and retry mechanisms in distributed systems

    • Basic understanding of observability concepts (metrics, logging, alerting)

    • Strong debugging, problem-solving, and system design skills

    Preferred Qualifications

    • Experience with asynchronous replication, disaster recovery (DR), or backup systems

    • Familiarity with object storage or large-scale data storage systems

    • Knowledge of delta encoding, change data capture, or incremental data synchronization techniques

    • Experience building high-throughput, low-latency data movement systems

    • Exposure to security practices including mutual TLS, encryption, and authentication

    • Experience working on enterprise-scale data platforms or storage products

    • Familiarity with performance optimization and large-scale system tuning

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