Software Engineer II, Backend - Data Cloud in New York, New York at 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.

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.

The team is focused on the following core domains:

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.

• Own the design and implementation of core backend services and APIs that power critical product capabilities and complex business logic.
• 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.
• Elevate the team's technical standards, lead code and design reviews, and mentor engineers on backend best practices.

• 2+ years of experience in a production environment using Python, Go, or a similar high-scale backend language.
• 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.
• Strong understanding of CS/algorithms fundamentals and experience with complex project delivery.
• Exceptional communication skills with technical and cross-functional stakeholders.

Rippling is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics. Rippling is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email accomodations@rippling.com

Rippling highly values having employees working in-office to foster a collaborative work environment and company culture. For office-based employees (employees who live within a 40 mile radius of a Rippling office), Rippling considers working in the office, at least three days a week under current policy, to be an essential function of the employee's role.

This role will receive a competitive salary + benefits + equity. The salary for US-based employees will be aligned with one of the ranges below based on location; see which tier applies to your location here. A variety of factors are considered when determining someone's compensation–including a candidate's professional background, experience, and location. Final offer amounts may vary from the amounts listed below.