Data Engineer - Data Platforms

Apply; Australia; On-site; AUD 150,000 - 190,000; Full time

Job summary

Xero is seeking a data platform engineer to design and build scalable data solutions from ingestion to modelling and platform tooling. You will own complex technical problems end to end, driving automation and high data quality across the system.

You will join a collaborative Data Engineering team that values strong engineering practices, IaC with Terraform, and close partnership with product and security teams to deliver trusted data products and self-service capabilities for the business.

Qualifications

• Hands-on experience with end-to-end data platforms.
• Experience with orchestration tools such as Snowflake, dbt, and Prefect.
• Infrastructure as code using Terraform.
• Proficient in AWS and building CI/CD pipelines.
• Strong data modelling, transformations, and data quality practices.

Responsibilities

• Design and build data solutions from ingestion through modelling and platform.
• Own complex technical problems end to end and drive reliability.
• Contribute to automation and self-service data capabilities.
• Collaborate with product and security teams to solve customer problems.

Skills

Snowflake

dbt

Prefect

Terraform

AWS

Data modelling

Data quality

CI/CD

Testing

Observability

Job description

The role

At Xero, our Data Platform team builds the pipelines, models, and infrastructure that turn raw data into products used across the company and by millions of small businesses worldwide. In this role, you will design and build data solutions at scale, from ingestion through to modelling and the underlying platform. You will own complex technical problems end to end, navigate ambiguity, and help lift both the engineering systems and the people around you.

You will play a key part in continuously raising our technical standards, driving better data quality, and creating a more self-service platform. Our team fosters an engineering culture that actively leans into automation and modern engineering practices, ensuring our foundations remain reliable and scalable as we grow.

The team

Our team sits within the Data Engineering organisation, which builds and operates trusted, scalable data foundations to power analytics, decision-making, and artificial intelligence across Xero. We are a collaborative group dedicated to delivering high-quality data products through robust engineering practices and a culture of empathy towards stakeholders. You will join an environment that values knowledge sharing, regular constructive feedback, and close collaboration with product and security teams to solve real customer problems.

The team is currently working on

• Expanding our core data platform capabilities and infrastructure using Snowflake, dbt, Prefect, and AWS to enhance observability and access management.

• Advancing our Infrastructure as Code practices by deploying and operating platform components with Terraform.

• Building out raw data intake pipelines and core data models that make information reusable and valuable for downstream teams.

• Developing real-time data products and behavioural analytics platforms using tools like Flink to enable advanced analytics and self-service capabilities.

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 are looking for

• You bring a strong understanding of end-to-end modern data platforms, including hands-on experience with orchestration and tools like Snowflake, dbt, and Prefect.

• Your background includes solid infrastructure as code practices, particularly using Terraform to build, deploy, and operate data platforms.

• You possess well-rounded core engineering habits, such as writing robust tests, implementing CI/CD pipelines, and working comfortably within AWS environments.

• You have a deep understanding of data engineering fundamentals, spanning data modelling, transformation, pipeline design, and data quality management.

• Your experience includes managing production systems, handling monitoring, incident response, and building automated, self-service tools to improve developer productivity.

• You demonstrate excellent problem-solving skills, strong ownership, and the ability to collaborate effectively with data consumers and engineering teams.