Senior Distributed Systems Engineer, Payroll Orchestration

Rippling; Toronto; On-site; CAD 250,000 - 437,000; Full time

Benefits offered by this job

Benefits

Equity

Job summary

Rippling is seeking a talented Distributed Systems Engineer to design and implement scalable payroll-related systems. You will build and maintain distributed services that power payroll processing across countries, using message queues, job flow systems like Temporal, and bi-temporal data models.

In this role you will collaborate with cross-functional teams, ensure observability and reliability, and work toward four or five 9s uptime on critical platform components.

Qualifications

• 8+ years of professional experience as a software engineer.
• Proficiency in a modern programming language (e.g. Go, Python).
• Comfortable at developing scalable and extendable core services and primitives with good abstractions that are used in many product flows.
• You have seen systems operating at a significant organizational scale.
• Solid understanding of message queues and job flow systems (e.g., Temporal, Kafka).
• Experience with DB transactional (e.g., Mongo, PostgreSQL) and analytical query engines (e.g, Snowflake, Clickhouse), and optimizing queries for performance.
• Excellent communication and collaboration skills.
• Ability to work independently and take ownership of projects, while also thriving in a team environment.

Responsibilities

• Design, develop, and implement distributed systems with a strong platform mindset.
• Write clean, maintainable, and well-documented code.
• Demonstrate expertise in concurrency control mechanisms and message ordering techniques to ensure data consistency in payroll processing.
• Utilize message queues and job flow systems (e.g Temporal) to orchestrate complex workflows related to payroll engine and payments processing, guaranteeing message delivery and job execution.
• Develop efficient data pipelines utilizing different transactional and analytical query engines to deliver fast data aggregates that power the payroll engine.
• Leverage bitemporal data modeling techniques to effectively manage payroll data flows.
• Collaboration: Work closely with cross-functional engineering teams to align on strategic goals and ensure successful project delivery.
• Observability: Implement comprehensive observability practices, including monitoring, logging, and tracing, to ensure system health and performance
• Resiliency and SLAs: Develop and maintain critical payroll platform systems with high availability and reliability, targeting four or five 9s uptime.

Skills

Go

Python

Distributed systems

Message queues

Temporal

Kafka

Concurrency control

Data pipelines

Tools

Temporal

Kafka

MongoDB

PostgreSQL

Snowflake

ClickHouse

Job description

Rippling is seeking a talented Distributed Systems Engineer to design and implement scalable payroll-related systems. You will build and maintain distributed services that power payroll processing across countries, using message queues, job flow systems like Temporal, and bi-temporal data models.

In this role you will collaborate with cross-functional teams, ensure observability and reliability, and work toward four or five 9s uptime on critical platform components.