
All-in-one platform for HR, IT, and Finance
Senior Software Engineer- Payroll Data at Rippling
About the role
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 $1.8B+ 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.
Why This Role
Rare Opportunity
Rippling is looking for a seasoned Senior Software Engineer to join the Payroll Data team, one of the most foundational teams in the Global Payroll organization. While other teams build features on top of payroll data, this team defines what that data looks like and how it gets materialized — decisions that shape the capabilities and constraints of the entire payroll product.
In this role, you will design and evolve the core payroll data models that represent earnings, deductions, taxes, and employer costs across dozens of countries. You'll architect materialization pipelines that transform payroll events into consistent, queryable datasets consumed by reporting, analytics and compliance. You'll define data contracts and interfaces that multiple teams depend on, and you'll make principled trade-offs between model expressiveness, query performance, and operational simplicity.
This is an opportunity to do work with deep technical leverage: a well-designed data model or a faster materialization pipeline doesn't just improve one feature — it improves every feature built on top of it.
What You Will Do:
- Own the design and evolution of payroll data models spanning earnings, deductions, taxes, contributions, and employer costs across 40+ countries, balancing correctness, extensibility, and query performance.
- Architect and scale materialization pipelines that transform raw payroll events and configurations into consistent, query-ready datasets for reporting, analytics, filings, and compliance.
- Define and maintain data contracts between the payroll data layer and its consumers — run management, tax engine, filings, object graph, RQL, and finance reporting — ensuring stability and clarity at every integration boundary.
- Tackle hard data modeling problems including temporal state management, multi-country regulatory variation, and bitemporal data patterns.
- Drive performance optimization across materialization and query paths, ensuring payroll data is available with the latency, freshness, and correctness guarantees that downstream systems require.
- Improve observability and operational tooling for data pipelines — monitoring for drift, staleness, schema violations, and materialization failures in a system where incorrect data has direct financial consequences.
- Lead cross-team technical discussions on data model changes, schema evolution, and materialization strategies that affect multiple payroll teams.
- Mentor engineers and raise the team's standards for data modeling rigor, pipeline reliability, testing, and documentation.
- Shape the long-term data architecture by working with stakeholders across payroll, platform, and analytics to anticipate new country launches, product features, and reporting requirements.
What You Will Have:
- 5+ years of professional software engineering experience with a strong focus on data modeling, data pipelines, or data platform work.
- Deep experience designing data models for complex, real-world domains — you think carefully about normalization, temporal state, schema evolution, and the trade-offs between flexibility and query performance.
- Strong backend engineering fundamentals, with experience in Python, Django, or similar stacks.
- Experience building and operating materialization or ETL pipelines — transforming event-driven or transactional data into consistent, queryable datasets at scale.
- Proven ability to design clean data contracts and interfaces consumed by multiple teams, with attention to backwards compatibility, versioning, and documentation.
- Strong debugging and problem-solving skills, particularly in systems where data correctness issues surface downstream and require tracing back through multiple layers.
- Comfort working in ambiguous, cross-functional environments where data model decisions require understanding both technical constraints and business domain nuance.
- Strong written and verbal communication skills; able to articulate modeling trade-offs, align partner teams on schema changes, and document data semantics clearly.
- Experience with payroll, fintech, HR tech, or regulated financial systems is a plus.
- Familiarity with bitemporal data patterns, event sourcing, or analytical query engines (e.g., Trino, Iceberg) is a plus.
Why This Role:
- Foundational leverage: Every payroll feature — runs, filings, reporting, analytics — is built on top of the data layer you own.
- Hard modeling problems: Temporal state, retroactive corrections, multi-country variation, and strict correctness requirements make this genuinely challenging data work.
- Platform impact: Your data model decisions shape what's possible for dozens of teams across the Global Payroll organization.
Communication matters: This role sits at the intersection of many teams — your ability to define clear abstractions and align stakeholders is as important as your code.
Additional Information:
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 dedicated to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email accommodations@rippling.com.
We highly value in-office collaboration to foster a cohesive work environment and company culture. For employees residing within a defined radius of a Rippling office, working on-site at least three days a week is considered an essential function of the role.
This position offers a competitive salary, comprehensive benefits, and equity opportunities. The exact salary will be determined based on factors such as experience, skills, and location.
Join us at Rippling and be a part of transforming how businesses manage performance-based compensation.
Required skills
Data modeling
Backend engineering
Distributed systems
Pipeline design
SQL
Domain modeling
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About Rippling

Rippling
Series CRippling is a privately owned international software company. Launched in 2017 in San Francisco, California, it operates a cloud-based software platform that allows businesses to manage their HR, finances, and IT matters.
501-1,000
Employees
San Francisco
Headquarters
$11.25B
Valuation
Reviews
1 reviews
2.7
1 reviews
Work-life balance
2.5
Compensation
3.0
Culture
2.5
Career
4.0
Management
2.5
35%
Recommend to a friend
Pros
Potential for multiple promotions
Career advancement opportunities
Cons
Work-life balance concerns
Negative company reputation
Poor employee satisfaction
Salary Ranges
3 data points
Intern
Intern · Data Scientist
0 reports
$190,000
total per year
Base
-
Stock
-
Bonus
-
$161,500
$218,500
Interview experience
3 interviews
Difficulty
3.3
/ 5
Duration
14-28 weeks
Interview process
1
Application Review
2
Technical Phone Screen
3
Virtual Onsite Interviews
4
Final Decision
Common questions
Coding/Algorithm
Technical Knowledge
Behavioral/STAR
System Design
Latest updates
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