Staff Software Engineer, Distributed Systems

The STAFF SOFTWARE ENGINEER, DISTRIBUTED SYSTEMS is responsible for designing and scaling distributed backend systems that support high-volume data synchronization. This role contributes to improving data processing throughput, system reliability, and performance across multi-cloud and multi-region infrastructures. The position is crucial for delivering scalable, fault-tolerant services that meet growing data and traffic demands, impacting the organization’s ability to maintain and expand its data integration capabilities., * Design, build, and scale distributed backend systems for data synchronization.

• Improve throughput, synchronization speed, reliability, and performance.
• Develop event-driven and streaming architectures using technologies like Kafka and message queues.
• Identify and resolve bottlenecks in distributed services, databases, and cloud infrastructure.
• Build systems to support significant growth in data volume and customer demand.
• Contribute to multi-cloud and multi-region infrastructure, including data residency compliance.
• Design low-latency services and caching systems for real-time data access.
• Collaborate with engineering teams and customers on scalability challenges.
• Own technical projects from architecture through deployment and optimization.
• Establish engineering practices to enhance observability, reliability, and maintainability.

• Minimum 7 years of professional software engineering experience with backend and distributed systems.
• Staff-level engineering capabilities demonstrated by technical ownership and system design.
• Experience in high-growth technology companies or startups.
• Strong knowledge of distributed systems architecture, scalability, fault tolerance, and performance optimization.
• Proven experience designing and scaling production systems handling substantial data volumes or throughput.
• Experience with event-driven systems, data pipelines, or synchronization services using Kafka and message queues.
• Familiarity with SQL databases, Docker, Kubernetes, and cloud production environments.
• Experience troubleshooting complex backend systems to improve reliability.
• Strong communication skills for cross-team collaboration.
• Ability to work remotely within U.S. or Canadian time zones.

Preferred Qualifications:

• Experience building data synchronization engines or processing large-scale data daily.
• Knowledge of streaming technologies such as Kafka, Spark, or Flink.
• Experience with multi-cloud, multi-region, and globally distributed infrastructure.
• Experience developing low-latency APIs, caching layers, or real-time personalization systems.
• Degree in Computer Science or related field.
• Active GitHub profile, technical portfolio, or relevant open-source contributions.

Pay Range and Compensation Package:

• Annual salary range: $180,000-$320,000.
• Competitive equity package.
• Remote-first work environment across the United States and Canada.
• High ownership and autonomy over technical projects.
• Opportunities to solve challenging distributed systems and large-scale infrastructure problems.

Benefits & Perks:

• Remote-first work environment.

Equal Opportunity Statement: Our client is an equal opportunity employer. They celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, or national origin.

Note:

RemoteHunter is a recruitment partner of this role. Please note that all employment decisions, including candidate assessment, interviews, hiring, compensation, and employment terms, are made exclusively by the hiring employer.

The organization operates in the technology sector, focusing on building high-scale data integration and synchronization systems. It addresses challenges related to processing and synchronizing large volumes of customer data reliably and efficiently across distributed backend systems. The company handles complex engineering problems involving streaming, performance optimization, system reliability, and multi-region cloud infrastructure, supporting growth in data volume and customer demand.