Senior Data Engineer

• Shape how the organisation thinks, learns, and makes decisions.
• Challenge yourself to shape, scale, and operate a next generation cloud data platform at enterprise scale.
• 12 Month initial Fixed-Term Contract role based at Jetstar HQ in Melbourne, with flexible hybrid working and Travel Benefit from Day one!

Jetstar thrives on innovation! We are always looking to employ ambitious and proactive professionals to help our business work smarter and more efficiently. You will be encouraged to think innovatively whilst developing and maintaining best practice.

We're searching for a Senior Data Engineer who wants to be more than a builder - someone who wants to shape how the organisation thinks, learns, and makes decisions. Our efforts are a key strategic enabler of a new way of working, one founded on experimentation, rapid iteration, and evidence based thinking.

You'll help evolve our Snowflake centric cloud data platform, building the reliable, secure, and observable foundations and advancements that allow teams to safely test assumptions, learn fast, and move with confidence. By creating platforms designed for speed, feedback, and trust, you'll directly enable decision science at scale and accelerate how insights turn into action across the business.

What you'll do:

• Design, build, and maintain scalable, high-performance data pipelines - maturing our Enterprise Data Availability and enabling our innovation pipeline.
• Drive and evolve Data Engineering/DataOps practices to improve data quality, delivery speed, and reliability across the data engineering lifecycle.
• Own data architecture and design decisions that balance performance, scalability, maintainability, and cost efficiency.
• Define data quality standards and ensures data assets are trustworthy, well-documented, and support confident decision making.
• Ensure data governance, security, and compliance requirements are embedded by design while enabling fast, safe delivery.
• Act as a senior technical authority, influencing data platform direction and uplifting engineering capability.

You'll bring:

• Tertiary qualification in Computer Science, Engineering, Information Technology, Data Science, or a related discipline, or equivalent practical experience.
• Relevant cloud and data platform certifications at a professional or advanced level are highly desirable, such as: Snowflake SnowPro Core / Advanced Architect, AWS Certified Solutions Architect - Professional / Data Analytics - Specialty.
• Formal training or certifications in Data Engineering, Data Architecture, or Cloud Data Platforms are advantageous.
• Demonstrated experience as a Senior Data Engineer or similar role within enterprise-scale or regulated environments.
• Experience building data platforms, analytics workloads, or data-intensive systems in cloud environments.
• Proven track record of influencing data architecture, standards, and engineering practices beyond immediate delivery tasks.
• Demonstrated ability to lead technical initiatives, mentor peers, and work well with business stakeholders.
• Deep expertise in cloud-native data architectures and distributed systems, ideally within large scale analytics environments.
• Strong hands on experience with modern data platforms (Snowflake preferred) including a strong understanding of data warehousing, data lakes, and lakehouse architectures.
• Proven capability designing and building data pipelines using ELT/ETL tools and orchestration frameworks (e.g. Snowflake, Fivetran, Apache Airflow).
• Experience with other data ingestion solutions (Apache NiFi Advantageous).
• Strong proficiency in SQL and Python for data transformation, pipeline development, and automation.
• Experience implementing data quality frameworks, testing strategies, and observability across data pipelines.
• Solid understanding of data modeling techniques (dimensional modeling) and schema design patterns.
• Working knowledge of data governance principles, including data lineage, cataloging, and metadata management.
• Experience with DataOps practices, including version control (Git), CI/CD for data pipelines, and deployment automation.
• Understanding of cloud data services and architectures - AWS preferred, including S3, Lambda, VPC, IAM, Private Networking and Airflow (MWAA).
• Collaborate with data consumers to understand requirements and deliver fit for purpose data solutions.
• Apply DataOps principles to automate testing, deployment, and monitoring of data pipelines.
• Document data lineage, definitions, and technical specifications to support data discovery and governance.
• Ensure adherence to data security, privacy, and compliance requirements in all data engineering work.
• Support and maintain our role based access control (RBAC/UBAC) security model to ensure secure access control to data.