Remote Senior Distributed Systems Engineer: Data Sync

Digitailor; United States; Remote; USD 180,000 - 320,000; Full time

Benefits offered by this job

Visa sponsorship

Remote work

Job summary

Digitailor is seeking an experienced backend engineer to own and deliver large-scale data syncing projects. You will design and operate distributed systems, building streaming capabilities and optimizing cross-region data movement in a high-growth environment.

Key responsibilities include reducing API latency, implementing caching layers, and expanding multi-cloud infrastructure while collaborating with customers on scaling challenges and reliability improvements.

Qualifications

• 7+ years backend experience with distributed systems.
• Experience building scalable data sync engines or streaming services.
• Strong systems design fundamentals and scaling capabilities.
• Production experience with Kafka, SQL databases, Kubernetes, Docker, and message queues.
• Experience at a high-growth startup and strong CS fundamentals.

Responsibilities

• Own projects from design through production delivery with autonomy.
• Build and optimize the core data syncing engine for large-scale movement.
• Develop streaming capabilities for real-time syncing from sources like webhooks and queues.
• Identify bottlenecks and design scalable solutions for growth.
• Improve API latency and build caching layers to meet performance goals.
• Extend multi-region/multi-cloud infra to support data residency.
• Collaborate with customers on scaling challenges and platform reliability.

Skills

Distributed systems

Backend engineering

System design

Communication

Learning agility

Tools

Kafka

SQL databases

Kubernetes

Docker

Spark

Flink

Job description

Digitailor is seeking an experienced backend engineer to own and deliver large-scale data syncing projects. You will design and operate distributed systems, building streaming capabilities and optimizing cross-region data movement in a high-growth environment.

Key responsibilities include reducing API latency, implementing caching layers, and expanding multi-cloud infrastructure while collaborating with customers on scaling challenges and reliability improvements.