Staff Engineer, Replication

Ddn; Raleigh (NC); On-site; USD 150,000 - 190,000; Full time

Job summary

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 for reliable disaster recovery in large-scale data systems.

You will develop high-performance replication pipelines, secure data transfer systems, and robust data integrity mechanisms, partnering with backend, security, and platform teams to deliver end-to-end

Qualifications

• 8+ years of experience in distributed systems, storage systems, or backend software engineering.
• Strong programming skills in 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.

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

Concurrency

Networking

Security

Observability

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