Data Engineer - Snowflake or Databricks

Data Engineer
AWS / Databricks or Snowflake. Sydney. $150k upto $200k + Super. Australian Citizens or Permanent Residents only.

• Full stack, no exceptions: infra, DataOps, platform engineering, the lakes themselves
• Senior engineers only, no exceptions: AWS plus Snowflake OR Databricks, $150k-$200k + super
• Bored doing easy work? Come argue about genuinely hard problems with seriously sharp peers

About the Client
A leading global professional services and consulting firm with a fast-growing Data and AI practice based in Sydney. They work across some of Australia's largest and most complex enterprise and government environments, on programs where the architecture actually matters and the technical bar is genuinely high. It's a business built around senior engineers who want to keep arguing about hard problems, not just keep shipping tickets.

About the Role
You don't measure your work by how many pipelines you've built. You measure it by how many unnecessary ones you avoided.

This isn't a role for someone who wants to stay in their lane. You'll work across the full stack: infrastructure, DataOps, platform engineering, and the data lakes themselves, on programs large enough that no single decision is trivial. Some engagements mean building a lake architecture from first principles; others mean pulling apart a platform that's accumulated years of shortcuts and making it defensible again. Either way, you're not executing someone else's design: you're the one senior enough in the room to make the call.

If you're good at this and quietly bored doing it somewhere that doesn't stretch you, this is built for people exactly like that.

Duties

• Own architecture and delivery across infra, DataOps, platform engineering and data lake design, working in AWS alongside either Snowflake or Databricks.
• Build and industrialise ETL and ELT pipelines using SQL, Python and PySpark, at a scale where shortcuts get found.
• Make and defend real architectural calls: data models, platform design, lake structure, and the trade-offs behind each.
• Work directly with client stakeholders as the technical authority in the room, not just the delivery resource.
• Collaborate with a senior bench of architects and engineers across multiple large, concurrent programs.

Requirements

• You've got senior-level data engineering experience, and a real track record of owning platforms end to end: architecture, delivery, the lot, not just stitching pipelines together and calling it done.
• You've got hands-on AWS experience, and it's genuine: you've made real decisions in it under real constraints, not just enough to talk your way through an interview.
• You're deep in either Snowflake or Databricks, not both. If you're claiming equal strength in both, we'll both know that's not quite true, and it'll show fast.
• You write SQL, Python and PySpark properly, and you're just as comfortable a level down in infra and DataOps as you are writing the transformation logic itself.
• You can hold your own technical position in a room full of senior client stakeholders, and argue it convincingly, without needing someone senior to back you up.
• You're an Australian Citizen or Permanent Resident. This one genuinely can't be worked around: we're not able to support visa sponsorship for this role, sorry.

How to Apply
If you're a senior data engineer who wants the full stack, not just another pipeline, we'd like to hear from you.