Senior Software Engineer - Payroll Data

Responsibilities

• 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, ensuring stability and clarity at every integration boundary.
• Tackle data modeling problems involving temporal state management, multi-country regulatory variation, and bitemporal data patterns.
• Drive performance optimization across materialization and query paths, ensuring required latency, freshness, and correctness.
• Improve observability and operational tooling for data pipelines, including monitoring for drift, staleness, schema violations, and materialization failures.
• Lead cross-team technical discussions on data model changes, schema evolution, and materialization strategies.
• Mentor engineers and raise standards for data modeling rigor, pipeline reliability, testing, and documentation.
• Shape long-term data architecture with stakeholders across payroll, platform, and analytics.

Requirements

• 5+ years of professional software engineering experience focused on data modeling, data pipelines, or data platform work.
• Experience designing data models for complex domains, including normalization, temporal state, schema evolution, and flexibility versus query performance trade-offs.
• Strong backend engineering fundamentals with experience in Python, Django, or similar stacks.
• Experience building and operating materialization or ETL pipelines at scale.
• Ability to design data contracts and interfaces consumed by multiple teams, including backwards compatibility, versioning, and documentation.
• Strong debugging and problem-solving skills for tracing data correctness issues across multiple system layers.
• Comfort working in ambiguous, cross-functional environments.
• Strong written and verbal communication skills, including articulating modeling trade-offs and documenting data semantics clearly.

Nice to Have

• Experience with payroll, fintech, HR technology, or regulated financial systems.
• Familiarity with bitemporal data patterns, event sourcing, or analytical query engines such as Trino and Iceberg.

Compensation and Benefits

• Competitive salary, comprehensive benefits, and equity opportunities.
• The exact salary is determined based on experience, skills, and location.
• 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.