Staff Data Engineer

We’re looking for an experienced software engineer specialising in data operations to help expand our data platform and create data tooling to do cool stuff. You’ll be joining a small team of Data and ML Engineers, tasked with managing Up’s data platform, keeping it stocked with fresh data, and building products on top of it for use in Up itself. We’re hell bent on automating just about everything that can be automated, and this role will play a big part in achieving that.

This is a rare opportunity to join our small but growing Data & ML team and have an outsized impact on the future of Up, Australia’s highest-rated banking app. Backed by Bendigo Bank, we operate with the speed of a startup and the scale of an established institution.

The role’s impact goes far beyond building yet more data pipelines. You’ll lead all manner of projects to create the tooling we need to make Up’s data footprint safer, its maintenance less reactive, more automated, and more useful for everyone using it across the organisation:

• You’ll be leading a push to automate as much manual work as possible, far beyond just the data platform itself. Think: making evidence gathering for audits automatic, proactive identification of sensitive data, moving ML training from infrequent local notebooks to fully hands-off every day.
• You’ll be pivotal in the continual development of our data platform and tooling. There’s so much more that’s possible beyond just moving data around, and that’s what we want to focus on.
• You’ll help scale our data products to cater for the ever-growing customer base of Up.
• You’ll be leading projects to migrate databases, those located on-prem and in GCP.
• Major projects will be yours to own from end-to-end. You can expect to have full ownership of designing and delivering solutions to our most complex data problems.
• We are very protective of the autonomy of our engineers, so you can expect to have plentiful time in the day to balance delivery, learning, and collaborating at your own pace.

Beyond the ownership of deliverables, we’ll also be looking to you to coach others about the best practices in data operations, modelling, and so on:

• When a challenge cuts across multiple teams, you're the one we'll turn to for clear architectural guidance to help solve it.
• When we have a gnarly problem like handling a continually changing schema dependency, we’ll look to you to help find the best solution.
• If you spot repeated manual data handling, you’ll be the one hunt down why it’s happening, educate people about how to automate it, and help them automate it entirely.

We're looking for someone with very strong software engineering skills which provide a foundation for building and using the right tools for the job. The successful candidate will have come from a software engineering background and have a demonstrated track record of applying those skills to data engineering.

Experience in some or all of the tools that we use will be beneficial, but we can give you the space to learn anything you don’t know already:

• Google Cloud is our cloud platform of choice, we use it to host Kubernetes clusters to host our applications, and our data lives in BigQuery and Postgres databases. All of that is managed with Terraform. At times you’ll be doing a whole lot of infrastructure work so experience in cloud platform engineering is a plus.
• Dagster orchestrates our tasks and dbt provides the framework for data modelling. Dagster is really cool, but experience with any modern orchestrator will get you most of the way to understanding it if you haven’t used it already.
• Most of our code is written in Python and SQL with a little dusting of Ruby and bash where necessary. Regardless of language, we’re looking for someone who is a master craftsman of software engineering and architecture.

• A software engineering background. We are only considering candidates who have worked in software engineering and have applied that skillset to data engineering.
• Experience managing the complexities of building, testing, and supporting software which handles moving, transforming, and using large amounts of data. We expect that you’ll be involved in all levels of the delivery process. Taking full ownership of projects and carrying them from the definition of requirements to handling production deployments.
• An opinion of what building good software is, particularly when it comes to the niche problems in data engineering. When designing tools with the team, you’ll be contributing your two cents on how we should test them, deploy them, maintain them, and structure them. Naturally, good communication skills will be key.
• Experience in designing and rolling out data platform tools and infrastructure. The amount of data that we are managing is rapidly growing and the things we use that data for are similarly exciting. What that brings is a need to expand the types of infrastructure we use
• An intrinsic motivation to upskill the engineers around you, increasing their awareness of software engineering and teaching them how to engineer data systems to the same high standard that we have for any other piece of software.
• An understanding of how data can be used beyond reporting; to automate processes across the organisation, to develop new features for Up’s customers, to glean insight into the future.

#LI-Hybrid