Principal Data Engineer
Principal-level data engineer leading Qantas' enterprise data platforms: designing scalable cloud data solutions, setting engineering standards, driving FinOps, and mentoring engineers. Core stack is Snowflake, AWS, dbt, SQL, Python, Airflow and Terraform, in a hybrid role at the Mascot campus in Sydney.
- Compensation
- Not disclosed
- Location
- Sydney, Australia
- Work setup
- Hybrid
- Seniority
- Principal
- Employment
- Contract
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Extensive data engineering / data platform experience in large, complex enterprise environments
- Proven experience leading enterprise-scale data engineering initiatives and influencing technical strategy
- Expert-level Snowflake knowledge: architecture, data modelling, security, governance, performance optimisation
- Advanced experience with AWS and cloud-native data architectures (data, storage, integration services)
- Deep expertise in dbt (core), SQL and Python with strong software engineering, testing and DevOps practices
- Extensive experience with orchestration/workflow tools such as Apache Airflow
- Strong knowledge of infrastructure-as-code and platform engineering using Terraform or similar
- Proven FinOps leadership: cost attribution, forecasting and optimisation across business domains
- Experience setting integration approach for complex enterprise ecosystems (SaaS, APIs, networking, security, legacy systems)
- Experience assuring engineering delivery across internal and partner teams (acceptance criteria, design reviews, production readiness)
- Experience establishing data quality, observability and data contract frameworks; operating production platforms incl. incident response and RCA
- Exceptional stakeholder engagement and communication skills for technical and non-technical audiences
- Ability to work through ambiguity, make sound technical decisions and document trade-offs
- Track record of mentoring and developing engineers
Nice to have
- Experience with Snowflake Openflow and Snowflake DCM
- Experience with Apache Kafka and event-driven architectures
- Experience with observability, governance and FinOps tools such as Datadog, Alation and Cloudability
- Exposure to AI, machine learning or advanced analytics platforms
Full description
- Exciting opportunity within our Data & Analytics team
- Permanent, full-time roles working at our Mascot Campus (hybrid working options available)
- Staff Travel Benefits from Day One!
The Principal Data Engineer plays a critical leadership role in shaping the future of Qantas' enterprise data platforms and engineering capabilities. Leveraging deep technical expertise and extensive experience in modern data architectures, you will drive the design, delivery and evolution of scalable, secure and cost-effective data solutions that enable trusted insights and business outcomes across the organisation. Working across the full lifecycle of our data platforms and products, you will influence strategic technology decisions, establish engineering standards that keep our data platforms reliable, observable and cost-effective
You will partner closely with Architects, Delivery Leads, Product Owners and senior business stakeholders to define technical direction, translate complex business requirements into scalable cloud-based solutions and drive enterprise-wide data initiatives. As a recognised technical leader, you will mentor engineers, conduct architecture and design reviews, and foster a culture of engineering excellence, continuous improvement and knowledge sharing across the Data & Analytics community.
Drawing on your experience with enterprise data platforms, cloud technologies and modern engineering practices, you will help shape the strategic roadmap for data engineering at Qantas while remaining close to the technology and guiding the adoption of emerging tools, platforms and capabilities that enhance our data, analytics and AI ecosystem.
What You'll Bring
- Extensive experience in data engineering, data platforms or related technology disciplines within large and complex enterprise environments.
- Proven experience leading enterprise-scale data engineering initiatives and influencing technical strategy.
- Expert-level knowledge of Snowflake, including architecture, data modelling, security, governance and performance optimisation.
- Advanced experience with AWS and cloud-native data architectures, including data, storage and integration services.
- Deep expertise in dbt (core), SQL and Python, supported by strong software engineering, testing and DevOps practices.
- Extensive experience working with modern orchestration and workflow management technologies such as Apache Airflow.
- Strong knowledge of infrastructure-as-code, automation and platform engineering practices using Terraform or similar tools.
- Proven FinOps leadership, including establishing cost attribution, forecasting and optimisation practices for cloud and data platform consumption across multiple business domains.