Data Engineer

About the role

Australian Payments Plus is hiring a Data Engineer in Sydney on a full-time basis. The role turns the data flowing through Australia's payments ecosystem into trusted, usable assets, designing, building and productionising secure, scalable data pipelines across a modern data platform. It is a hands-on engineering position working with large and complex datasets, using Snowflake, AWS, Python, SQL, APIs and real-time data.

Key responsibilities

• Design, build, deploy and maintain scalable batch and real-time data pipelines that ingest, transform and make large datasets available for business use.
• Build ingestion pipelines integrating data from APIs, databases, files, event streams and third-party platforms.
• Design pipelines for reliability, scalability, performance and maintainability.
• Implement orchestration, observability, error handling, reconciliation and recovery mechanisms.
• Apply incremental processing, CDC and event-driven integration patterns where appropriate.
• Apply strong governance and security practices to payment and transaction data.
• Develop tables, views, schemas, stored procedures and other Snowflake objects, and tests to validate data quality and transformation logic.
• Monitor and optimise pipeline and platform performance, troubleshoot technical issues.
• Provide on-call support as part of a rotational roster.

Required profile

• 2+ years of hands-on experience building and maintaining enterprise or bank-grade data infrastructure, ideally in payments, banking or financial services.
• Experience connecting and operationalising data across warehouses, lakes, streaming platforms and analytics tools, with attention to performance, scalability and reliability.
• Curious, collaborative engineering mindset, comfortable working autonomously in Agile teams and partnering with analysts and business stakeholders.

Required skills

• Snowflake, SQL and NoSQL data stores, including complex queries, transformations, data warehousing and large-scale data manipulation.
• Cloud databases, DBT and orchestration tools such as Airflow; event streaming platforms such as Kafka.
• Strong Python and experience building data pipelines and integrations via APIs, ETL and cloud infrastructure such as AWS.
• Data modelling, data quality, reconciliation, governance and security.

The Talent Acquisition team reviews applications and notifies candidates of the outcome within two weeks. The company states it does not partner with recruitment agencies for this role.