Staff Replication Development Engineer

DDN; North Carolina; Hybrid; USD 120,000 - 170,000; Full time

Job summary

DDN seeks a Staff Replication Development Engineer to lead the design and development of the replication engine for the Infinia AI Data Platform. You will build high-performance asynchronous replication capabilities that enable reliable disaster recovery and scalable data movement across large-scale data systems.

The role demands deep expertise in distributed systems, multi-threading, secure data transfer (TLS), and collaboration with backend, security, and platform teams to deliver end-to-end

Qualifications

• 8+ years of experience in distributed systems or backend software engineering.
• Proficient in one of: C++, Go, Java, or Rust.
• Experience designing data replication systems and distributed data services.
• Strong understanding of distributed systems concepts (consistency, availability, scalability, fault tolerance).
• Experience with multi-threading, concurrency and parallel processing.
• Knowledge of TLS and secure communication (TLS).
• Experience designing and building REST APIs and service-based architectures.

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.

Skills

Distributed systems

C++

Go

Java

Rust

Multi-threading

REST APIs

TLS security

Data replication

Troubleshooting

Job 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