Senior Software Engineer, Backend - Data Cloud

About Rippling

Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.

Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.

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.

We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses.

About the Data Cloud Team

Rippling Data Cloud is a new suite of products that aggregates data from across your company into Rippling, connects it to worker identity, and makes it available for analysis, visualization and action. 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. It understands how all of that data relates to employees, managers, departments, locations, cost centers, permissions, and historical changes in your ever-changing business. 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. Here’s how they relate:

Data Cloud provides the unified data that AI reasons over:
Rippling AI leverages the Employee Graph and all platform data (payroll rules, earnings types, deduction logic, permissions, etc.) as its source of truthBecause Rippling is a unified platform rather than stitched-together acquisitions, the data is clean, consistent, and complete which makes AI answers accurate and context-awareAI respects the same permissions model as the rest of the platform, so it only surfaces data the user is authorized to see

The Rippling AI unlocks advanced Data Cloud capabilities:

• AI Dashboards: build dashboards from scratch using natural language prompts
• Transformations: full publish access
• Pipelines: ingest data via managed connectors
• Lineage & Catalog: explore data lineage for reports
• Advanced features: parameters, SQL queries, and the ability to incorporate third-party data

Why this matters

Most HR/Finance systems weren’t built for AI. Their data is messy and fragmented. Rippling AI is described as the first “context-aware, senior analyst” for HR and Finance teams because it sits on top of a unified data model (Data Cloud + Employee Graph) that actually understands your business logic end-to-end.

What We Build

The team is focused on the following core domains:

• Analytics – Focuses on the reporting and dashboarding products that enable users to visualize and analyze data within Rippling.
• Data Access – Owns the query engine (RQL, Rippling Query Language) that powers data retrieval across the platform. This area includes sub-teams responsible for query execution, data ingestion, and query history.
• Data Management – Owns the metadata and data catalog layer, including how data assets are discovered, governed, and documented.
• Ingest & Prep – Responsible for bringing external data into Rippling. This area includes Managed Connectors (pre-built integrations with third-party systems) and Transformations (data shaping and preparation).
• Insights – A newer area within Data Cloud focused on surfacing actionable insights from data.

What You’ll Do

• Work on distributed processing engines and distributed databases
• Develop high-quality software with attention to detail using tech stacks like Python, MongoDB, CDC, and Kafka
• Leverage big data technologies like Aurora, Trino, Presto, Pinot, Iceberg, Flink and more.
• Build custom programming languages within the Rippling Platform
• Create data platforms, data lakes, and data ingestion systems that work at scale
• Design, develop, code, and test …