Senior Data Engineer (Scala/Java, Spark, AWS)

Program Overview

We are embarking on an exciting Data Transformation program and are ready to push the boundaries and deliver engineering best practices to elevate the data quality and availability in our domain. Together we will build tomorrow’s bank today, using world-leading engineering, technology, and innovation.

Key Responsibilities

• You have knowledge and experience that spans both development and architecture, including data engineering, modelling and cloud architecture.
• Build and evolve our data and software engineering platforms, delivering scalable, resilient solutions in a cloud‑based environment.
• Independently deliver well‑scoped technical solutions from design through build, testing, release, and support while seeking input early when problems are ambiguous or cross‑cutting.
• Engage with business and technical stakeholders to translate requirements into clear, pragmatic technical designs.
• Mentor and share knowledge through pairing and constructive code reviews.
• Step up to provide staff‑like ownership for a small initiative when required.

Qualifications

• Strong, hands‑on experience with Scala or Java for building large‑scale, distributed data and software systems.
• Experience designing and implementing solutions on AWS, leveraging cloud‑native services for scalable and resilient architectures.
• Solid foundation in data engineering, including ETL pipeline design, data modelling, and large‑scale data processing.
• Strong experience with Apache Spark (EMR experience is a plus) and distributed data processing frameworks.
• Ability to handle and process large data volumes efficiently, balancing performance, scalability, reliability, and cost.
• Experience orchestrating pipelines, including dependency handling, retries, and operational resilience.
• Performance tuning and optimisation across Spark workloads and cloud infrastructure.
• Experience designing and implementing automated testing approaches for data and software systems, including unit testing, integration testing, testing of Spark jobs, data quality validation, and regression testing.
• Strong understanding of secure data engineering practices, especially with high‑risk or sensitive data.
• Hands‑on experience implementing data security controls such as encryption at rest and in transit, secrets management, data masking, and fine‑grained access control.
• Knowledge of software engineering best practices such as CI/CD, automated testing, code reviews, and version control (GitHub).
• Ability to produce clear technical documentation and lightweight design artefacts for engineers and for architecture/cyber security review.
• Experience working with agile delivery practices and tools such as JIRA and Confluence.
• Certification: Either Quantexa certification (Data Engineering or Scoring) or an AWS certification is desirable.
• Experience with Quantexa platforms, upgrades, or financial crime data domains is advantageous.

Benefits & Culture

Our people bring diverse backgrounds and unique perspectives to build a respectful, inclusive, and flexible workplace. We support flexible work locations and offer options such as changing start and finish times, part‑time arrangements, and job share. We focus on delivering a positive impact for customers, communities, and each other. Engineering roles are open nationwide, with technology hubs in Melbourne and Perth.