Principal Engineer — Payroll Engine & Data Systems

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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.

Your Pedigree

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."

The "Hard" Requirements

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).

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Company: Ebury

Apply for the Principal Engineer — Payroll Engine & Data Systems

Location: London

Job Description:

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.

Your Pedigree

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.”

The “Hard” Requirements

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).

#J-18808-Ljbffr…

Posted: May 20th, 2026