Staff Distributed Systems Engineer - Global Payroll Platform

Rippling (Netherlands); Seattle (WA); On-site; USD 180,000 - 315,000; Full time

Benefits offered by this job

Competitive salary + benefits + equity

Job summary

Rippling is seeking a Distributed Systems Engineer to join our core payroll team and design scalable systems powering payroll across multiple countries. You will focus on concurrency, data pipelines, and robust workflows using Temporal and Kafka, delivering reliable payroll processing.

You’ll collaborate with cross-functional teams to ensure high availability and observability, while maintaining four to five nines uptime in a fast-growing environment.

Qualifications

• 8+ years of professional software engineering experience.
• Proficiency in Go and/or Python.
• Experience designing scalable distributed systems.
• Strong understanding of concurrency control and message ordering.
• Experience with message queues and job flow systems (Temporal, Kafka).
• Experience with DB transactional and analytical engines (Mongo, PostgreSQL, Snowflake, ClickHouse).
• Excellent communication and collaboration skills.

Responsibilities

• Design and implement distributed systems with a platform mindset.
• Write clean, maintainable, well-documented code.
• Ensure data consistency with concurrency and message ordering techniques.
• Use Temporal and Kafka to orchestrate payroll workflows and payments processing.
• Build efficient data pipelines for fast payroll data aggregates.
• Apply bitemporal data modeling for payroll data flows.
• Collaborate with cross-functional teams to align on goals.
• Implement observability: monitoring, logging, tracing.
• Maintain high availability with strict SLAs.

Skills

8+ years

Go

Python

Distributed systems

Concurrency control

Temporal

Kafka

Data pipelines

Tools

Temporal

Kafka

MongoDB

PostgreSQL

Snowflake

ClickHouse

Job description

Rippling is seeking a Distributed Systems Engineer to join our core payroll team and design scalable systems powering payroll across multiple countries. You will focus on concurrency, data pipelines, and robust workflows using Temporal and Kafka, delivering reliable payroll processing.

You’ll collaborate with cross-functional teams to ensure high availability and observability, while maintaining four to five nines uptime in a fast-growing environment.