About Us

We’re known for being the country’s most popular rewards program, helping over 10 million Australians get more of what they value beyond the checkout. And through our extended network of partnerships with other nationally recognised brands, we make every day simpler, easier and more rewarding for our members. Plus, we’re also the winner of Canstar Blue's 2023, 2024 and 2025 Most Satisfied Customer award for Rewards Programs

But,we'remorethan the card you carry around in your wallet or the app on your phoneOur diverse team islocatedall over Australia, and our incredible office islocatedright in the heart of Melbourne CBD.Staying true to our versatile working policy and people-centric culture, we ensure all our team members are set up to work remotely across Australia. We are outcomes-focused, and everything we do is aligned with our core principles - Own, Act and Inspire.

Your Team

We've already built a pretty amazing team, but we're not looking for more of the same. Our day-to-day is made stronger when we surround ourselves with people who are different, like you.

Your Role

The Principal Data Engineer owns the technical approach and end-to-end engineering of data platforms and data products, from discovery through design, delivery, secure operation and improvement. The role combines hands-on data engineering with people leadership, enabling reliable, governed data that delivers measurable value for members, partners and Flybuys.

- Responsible for the design and implementation of data engineering platforms, maintaining and improving infrastructure as code capabilities for scalable and efficient data solutions.
- Lead, manage and develop data engineers through coaching, feedback, reviews and reusable examples.



Coach Senior/Lead Data Engineers and Data Quality engineer where assigned.
- Design and implement reusable data models, ingestion, transformation and streaming pipelines, and data architectures that balance consumer needs, reliability, security, cost and performance.
- Define and maintain data engineering governance and technical standards for data quality, integrity, lineage, access controls, privacy, security and operability. Embed these guardrails in delivery and operation, aligned with data governance policies and relevant assurance teams.
- Evaluate emerging data engineering methods and technologies and use approved AI-assisted engineering and automation to improve development, testing, documentation and operations within privacy, security and governance requirements.
- Partner with Product Management, Squad Leads, architects, business stakeholders, analysts and data scientists to frame data opportunities, validate assumptions and compare options. Constructively challenge choices against value, usability, feasibility, viability, risk, cost and delivery pace.
- Own data engineering initiatives from discovery and design through build, release and production improvement. Guide estimates, sequencing, dependencies and blocker resolution, making readiness, risks and trade-offs transparent.
- Ensure data platforms and pipelines are observable, testable, resilient and supportable.



Establish monitoring, data quality checks, incident response and performance expectations before release, and resolve complex production issues through root-cause analysis.
- Enable flex squads and other teams to build and support their own data pipelines through governed self-service, providing design reviews and hands‑on support to ensure standards and production-readiness requirements are met. Partner with Architecture, Security and Platform teams on novel, complex, high‑risk, cross-domain or enterprise decisions.
- Contribute technical leadership beyond the immediate team, shaping coordinated data and technology roadmaps and making technical debt, reliability and security risks, costs and operational constraints visible for prioritisation.
- Undertake other reasonable accountabilities and deliverables assigned by management.

Your Experience

- Bachelor’s or Master’s degree in computer science, Data Science, Engineering, or a related field.
- 8+ years of experience in data engineering, with at least 2 years in a team leadership or management role, including significant experience delivering complex data products or platforms and owning their full engineering lifecycle.
- Extensive experience in designing, building, and managing data pipelines, data warehouses, and data lakes.
- Hands‑on experience with cloud data warehouses (e.g., Google BigQuery, Snowflake) and related technologies.
- Strong proficiency in SQL and Python, with experience in other relevant languages.
- Knowledge of data governance, data quality, lineage and data security, including privacy, compliance, risk management and access controls throughout the data life

📌 Principal Data Engineer Hybrid (Melbourne)
🏢 Flybuys
📍 Melbourne