Principal Engineer – Data

Role Overview

• Designing and building a modern, composable data platform on open standards — choosing the right patterns for ingestion, storage, transformation, and query to serve a range of analytical and operational workloads.
• Building real-time streaming data pipelines that deliver near-instant data freshness from source events through to query-ready datasets.
• Creating the data infrastructure that enables AI and agentic capabilities — on-demand compute, isolated query environments, and semantic layers that make data accessible to both humans and intelligent systems.
• Enabling enterprise customers to securely access their payroll data inside their own BI tools, without data duplication or added operational overhead.
• Implementing fine-grained authorisation across the data layer — multi-tenant isolation, role-based access, and sensitive data handling that meet the strict privacy requirements of payroll.
• Building layered data transformation models that power reports, and analytics — from raw event streams through to curated, business-ready datasets.
• Defining and enforcing data contracts across domain teams, treating data as a product with clear ownership, quality standards, and SLAs.
• Championing data sovereignty, immutability, and point-in-time query capabilities for audit and compliance.
• Leading the technical relationship with external data platform partners, ensuring effective knowledge transfer and growing internal capability.
• Mentoring engineers, establishing data engineering practices, and contributing to architectural decisions across the broader platform.

Requirements

• Deep experience with modern data engineering — data lakes or lakehouses, columnar storage formats, and layered transformation architectures.
• Strong SQL skills and hands-on experience with analytical query engines.
• Experience building and operating real-time or near-real-time data pipelines using event streaming platforms.
• Familiarity with data transformation frameworks and an understanding of data contracts and schema governance.
• Proficiency with cloud data infrastructure (Azure preferred) — object storage, container orchestration, secrets management, and monitoring.
• Strong understanding of multi-tenant data security — tenant isolation, role-based access control, PII handling, and data sovereignty requirements.
• Experience designing data platforms that serve both operational and analytical workloads — you know the difference between ELT and ETL and when each pattern applies.
• Proficiency in Python and/or TypeScript for pipeline development and automation.
• Track record of making sound architectural decisions in ambiguous, greenfield environments.
• Excellent communication skills — you can translate complex data architecture decisions into language that product, security, and leadership stakeholders understand.

Tech Stack

• Azure
• Cloud
• ETL
• Python
• SQL
• TypeScript