Staff Data Engineer (Data Architect) - Sydney/Melbourne

The role

You will lead the technical direction for our real-time streaming and analytics team, owning the architecture behind how we move financial and behavioral data at scale and making the design calls that keep our systems reliable as they grow. This position spans the full data lifecycle, from ingestion and streaming through data modeling, warehousing, and the data apps stakeholders use.

Much of your impact comes through others. You will partner with tech leaders across data engineering, including the platform, data modeling, and data engineering teams, and product teams like Auto Bank Reconciliation, while lending your expertise to other data products. You will not manage people, but you will raise the bar around you by mentoring engineers, reviewing designs, aligning teams on shared patterns, and turning hard problems into reusable solutions. Your work shows up directly in the product, from bank reconciliation that saves small businesses hours each week to the analytics that shape what we build next.

The team & how they connect

Our team sits in the data engineering organization, building and operating trusted, scalable foundations so teams can easily discover, access, and use reliable products to power analytics, decision-making, and artificial intelligence. We are a collaborative group dedicated to delivering high-quality data solutions through strong engineering practices and a culture of continuous empathy towards stakeholders. You will join a supportive group that values knowledge sharing, regularly provides constructive feedback, and works closely with product and security teams to manage dependencies and solve real customer problems.

The team is currently working on

• Designing, building, and operating a robust data streaming solution to support real-time data processing needs
• Creating data models and vault structures that keep data consistent, reusable, and easy to build on across products
• Improving the operational performance and reliability of data products by monitoring stability and meeting service level objectives
• Shaping architectural design decisions and advancing DataOps tools to accelerate the delivery of high-quality data products

Where and how you can work

We support a flexible working model that empowers you to balance your professional and personal life. You will have the option to work in a hybrid capacity, combining the focus of remote work with the collaboration of our office spaces and team boost days to foster connection and alignment.

Here are some of the things we're looking for, for this role:

• You will bring deep expertise in designing and operating large-scale data platforms across the entire lifecycle, including ingestion, modeling, warehousing, and applications.
• Your background will showcase a strong understanding of defining enterprise architecture, standards, and integration patterns for batch streaming, APIs, and event-driven architectures.
• A strong grasp of data governance, metadata, lineage, security, and privacy by design will be essential for your success.
• You possess fluency across the modern data stack, such as Snowflake, Kafka, dbt, and cloud infrastructure, alongside a curiosity to keep learning.
• Your approach includes strong hands on engineering capability where you continue to build, review, debug, and set the standard by doing.
• You offer strong stakeholder management skills and the ability to influence technical direction through clear communication and sound architectural decisions.