Principal Engineer (Payroll Engine & Data Systems)

Requirements

• The Full-Stack Backend Mindset: You are equally comfortable optimizing a recursive SQL query as you are designing a resilient webhook listener or a topological sort algorithm
• Data Pipeline Veteran: You have experience with ETL/ELT patterns, data validation frameworks, and ensuring Exactly-Once processing in financial systems
• Domain Expertise: You’ve built at Deel, Rippling, Papaya Global or similar Tech-first Global Payroll and Payments company, and you understand that “Integrations” aren’t just about APIs—they’re about mapping conflicting data models across cultures
• Architectural Leadership: You can bridge the gap between “Product needs this integration tomorrow” and “Our data model needs to remain pure for the next 5 years.”
• Deep Polyglot Backend Skills: Expertise in Python (for the engine) and Node.js/TypeScript (for the integration layers)
• PostgreSQL Mastery: You understand bitemporality, window functions, and how to manage schema evolution in a multi-tenant SaaS environment
• Location: London (Preferred), Madrid, or Malaga (4 days/week in-office)

What the job involves

• We are building more than a calculation engine; we are building an integrated global financial ecosystem
• As a Principal Engineer, you will own the end-to-end lifecycle of payroll data—from the moment an employee is onboarded in a third-party HRIS, through our deterministic bitemporal calculation engine, to the final generation of global payment files and statutory reporting
• You are an architect who writes code, a data engineer who understands state, and an integration expert who knows that a payroll system is only as good as the data flowing into it
• The Stack:
• Core Engine & Data: Python (NetworkX, Pydantic, Decimal), PostgreSQL (Bitemporal modeling, dbt for analytics)
• Integrations & Pipelines: Node.js/TypeScript, Event-sourced architecture (Message Queues, Webhooks)
• The Ecosystem: Deep integrations with HRIS/HCMs (Workday, HiBob, BambooHR) and Ebury’s Payments architecture
• AI-Augmentation: Claude Code for development and AI-driven data extraction
• What You’ll Own (The End-to-End Scope):
• The Calculation Engine: Design the DAG-based resolver and bitemporal logic to handle complex, multi-jurisdictional payroll math with 100% accuracy
• Data Ingestion & Transformation: Architect the pipelines that ingest messy, unstructured data from fragmented HRIS sources and transform it into our deterministic PayrollRuleSchema
• Third-Party Integrations: Build robust, API-first connectors and “Outbox” pattern event systems to sync data across the global HR/Fintech stack
• The Payment & Reporting Rail: Own the generation of complex output artifacts—from ISO 20022 payment files to localized tax filings and GL (General Ledger) reports
• Bitemporal Data Strategy: Ensure the entire data lake supports “As-Of” reporting, allowing users to reconstruct the state of any payroll run at any point in history

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