Principal Data Engineer

At Nine, we build and manage the pipelines, applications, and infrastructure that power our data-driven future. As a Principal Data Engineer, you will be the technical authority and architect for our core data platforms, tackling our most significant challenges in data warehousing, modelling, and governance.

This is a hands-on technical leadership role for a seasoned expert who will set the vision for our data architecture. You will be instrumental in evolving our technical direction, elevating the skills of the entire data engineering team, and creating "golden path" examples that define excellence. Your work will directly influence our ability to derive insights and build intelligent products at scale.

Reporting to the Director of Technology - Data & AI, you will operate as a key technical authority and a peer to our data engineering managers and senior data product managers, providing the thought leadership that underpins our entire data strategy.

As the Principal Data Engineer, you will:

• Own the architectural vision for data: Continuously evolve our approach to data warehousing, data modelling (e.g., Kimball, Inmon, Data Vault), and data governance, establishing the patterns that will be used across the organisation.

• Serve as a Centre of Excellence: Act as a go-to expert for data engineering, providing practical advice, guidance, and mentorship to engineers across multiple teams and fostering a culture of technical excellence.

• Provide thought leadership and strategy: Design resilient, scalable data architectures that anticipate future needs. Lead initiatives on data governance, including cataloging, data quality, access management, and the build of a central semantic layer.

• Champion GenAI for Engineering Excellence: Drive the adoption and establish best practices for using Generative AI tools to boost engineering productivity and efficiency. This includes leveraging platforms like GitHub Copilot for code development and BigQuery's GenAI capabilities for accelerated data analysis and discovery.

• Lead by example on complex projects: Embed directly into our most critical projects to lead the design and architecture of scalable and performant data models, ensuring solutions are robust and fit within the broader organisational context.

• Drive technical innovation: Run proof-of-concepts for new technologies and patterns, developing standards for data transformations and pipeline development that other engineers will follow.