Staff Replication Development Engineer
DDN · Hybrid
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Job details
- Work model
- Hybrid
- Salary
- Not listed by source
- Location
- Remote - North Carolina
What the role asks for
What you'd do
- 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
What they're asking for
- 8+ years of experience in distributed systems, storage systems, or backend software engineeringExperience
- Strong programming skills in one or more languages: C++, Go, Java, or RustSkill
- Experience designing and building data replication systems, data pipelines, or distributed data servicesSkill
- Deep understanding of distributed systems concepts (consistency, availability, scalability, fault tolerance)Skill
- Strong expertise in multi-threading, concurrency, and parallel processingSkill
- Knowledge of networking protocols and secure communication (TCP/IP, HTTP/HTTPS, TLS)Skill
- Experience implementing data integrity mechanisms (checksums, validation, consistency checks)Skill
- Experience designing and building REST APIs and service-based architecturesSkill
- Familiarity with checkpointing, failure recovery, and retry mechanisms in distributed systemsSkill
- Basic understanding of observability concepts (metrics, logging, alerting)Skill
- Strong debugging, problem-solving, and system design skillsSkill
- Experience with asynchronous replication, disaster recovery (DR), or backup systemsSkillPreferred
- Familiarity with object storage or large-scale data storage systemsSkillPreferred
- Knowledge of delta encoding, change data capture, or incremental data synchronization techniquesSkillPreferred
- Experience building high-throughput, low-latency data movement systemsSkillPreferred
Parsed by MeritLog from the employer’s own posting. The full description follows below.
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