Rippling

Software Engineer II, Backend - Data Cloud

Seattle, WA · Mid

Sponsorship not specifiedDetected 3 days ago

PythonGoDistributed SystemsBackend DevelopmentAlgorithmsSQLRESTCommunication

About the role

Based in San Francisco, CA, Rippling has raised $1.4B+ from the world's top investors-including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock-and was named one of America's best startup employers by Forbes.

Own the design and implementation of core backend services and APIs that power critical product capabilities and complex business logic.
Elevate the team's technical standards, lead code and design reviews, and mentor engineers on backend best practices.
build dashboards from scratch using natural language prompts

parameters, SQL queries, and the ability to incorporate third-party data Why this matters Most HR/Finance systems weren't built for AI.
What you will need 2+ years of experience in a production environment using Python, Go, or a similar high-scale backend language.
Strong understanding of CS/algorithms fundamentals and experience with complex project delivery.

About Rippling Rippling gives businesses one place to run HR, IT, and Finance.
Take onboarding, for example.
Please be aware that all official communication will only be sent from @ Rippling.com addresses.
It preserves and enriches data context to enable precise and accurate answers to your most important and nuanced business questions.
It's a complete data stack including data connectors, transformations, visualizations, AI-powered analytics, and even inbound Zero-Copy.
That makes it possible to ask questions that traditional BI systems struggle to answer correctly.
Data Cloud as the foundation for Rippling AI Data Cloud and AI are deeply connected in Rippling.
Data Cloud is the data infrastructure layer that powers Rippling AI.

Analytics - Focuses on the reporting and dashboarding products that let users visualize and analyze data within Rippling.
Data Access - Owns the query engine (RQL - Rippling Query Language) that powers data retrieval across the platform.
Includes sub-teams for query execution, ingestion, and history.
Data Management - Owns the metadata and data catalog layer - how data assets are discovered, governed, and documented.
Ingest & Prep - Responsible for bringing external data into Rippling - includes Managed Connectors (pre-built integrations to third-party systems) and Transformations (data shaping and preparation).
Insights - A newer area within Data Cloud focused on surfacing actionable insights from data.
Ensure all systems are built for high-volume scale, reliability, and security, making strategic decisions about infrastructure and data integrity.
Work seamlessly with product, frontend, and platform teams to translate feature goals into robust, high-performance technical solutions.
Deep expertise in distributed systems architecture, data modeling, and performance optimization of relational databases.
Experience contributing to systems operating at significant technical and organizational scale.

This listing is sourced directly from Rippling's careers page and normalized into a canonical job model.