Role Overview
You will lead the technical direction for our real‐time streaming and analytics team, owning the architecture behind how we move financial and behavioural 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 modelling, warehousing, and the data apps stakeholders use.
Responsibilities
Partner with tech leaders across data engineering, including platform, data modelling, and data engineering teams, and product teams like Auto Bank Reconciliation, to guide design choices and raise standards.
Mentor engineers, review designs, align teams on shared patterns, and turn hard problems into reusable solutions.
Shape architectural decisions and advance DataOps tools to accelerate delivery of high‐quality data products.
Design, build, and operate robust data streaming solutions to support real‐time data processing needs.
Create data models and vault structures that keep data consistent, reusable, and easy to build on across products.
Improve operational performance and reliability of data products by monitoring stability and meeting service level objectives.
Qualifications




Deep expertise in designing and operating large‐scale data platforms across the entire lifecycle, including ingestion, modelling, warehousing, and applications.
Solid understanding of defining enterprise architecture, standards, and integration patterns for batch, streaming, APIs, and event‐driven architectures.
Proven grasp of data governance, metadata, lineage, security, and privacy by design.
Fluency across the up-to-date data stack, such as Snowflake, Kafka, dbt, and cloud infrastructure.
Hands‐on engineering capability to build, review, debug, and set standards by doing.
Strong stakeholder management skills and ability to influence technical direction through clear communication and sound architectural decisions.
Team & Culture
Our team sits in the data engineering organisation, building and operating trusted, scalable foundations so teams can easily discover, access, and use reliable products to power analytics, decision‐making, and AI. We value knowledge sharing, constructive feedback, and partnership with product and security teams.
Location
We support a versatile working model. You may work in a hybrid capacity, combining remote focus with collaboration in our office spaces and team boost days.
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📌 Staff Data Engineer Data Architect Sydney/melbourne (Australia)
🏢 Xero
📍 Australia