Senior Data Engineer
Summary
Lead-level Data Engineer at a global consulting firm in Sydney, designing and delivering data platforms for government, financial services and enterprise clients. Core stack is Databricks and/or Snowflake on AWS, with Terraform, dbt, CI/CD and AI-accelerated engineering in technical lead, principal engineer or hands-on architect roles.
Salary: $168k - $224k p.a. + + Super + Bonuses
Lead Data Engineer - Databricks, Snowflake & AWS
Sydney | Permanent | $150k - $220k + super | Global consulting firm - Data Infrastructure, Platform & Analytics
If you've ever lost an afternoon to a Spark job that should have run in four minutes, or rebuilt a pipeline because the first version bugged you - keep reading.
Our client's Data Infrastructure, Platform & Analytics team is growing in Sydney. It's a chance to take your thinking about how data platforms should be built and apply it to large, complex programs of work - where it shapes the outcome, not just the ticket in front of you.
The work
You'll design and deliver data platforms for government, financial services and enterprise clients, on programs big enough that the architecture decisions matter.
This is consulting, so expect variety - different clients, different data estates, different problems. The upside is influence. You'll be in the room when platform direction gets set, working alongside client technology leaders, and accountable for whether it works.
The team works AI-accelerated - AI tooling is built into how platforms are designed, built and delivered, so you spend less time on boilerplate and more on the problems worth solving.
Where you fit
Every role is at technical leadership level. That doesn't mean you stop building.
- Technical Lead - you own platform components end to end and make the design calls. Prior people leadership isn't required - strong individual contributors who set the technical standard for others are exactly who we'd like to hear from.
- Principal Engineer - you lead delivery across a domain, mentor engineers and shape how a client's platform is built.
- Hands-on Architect - you design target-state architecture, own the cost, governance and scalability tradeoffs, and still get your hands dirty.
What you'll bring
- Real depth in Databricks - Spark/PySpark, Delta Lake, Unity Catalog, Workflows - and/or Snowflake - warehouse sizing, Snowpipe, Streams & Tasks, Snowpark. Strength in one with working knowledge of the other is the sweet spot.
- Hands-on AWS data platform experience - Glue and/or Redshift in particular, plus the surrounding services (S3, Lambda, Step Functions, IAM)
- Strong SQL and data modelling, with dbt experience valued
- Infrastructure-as-code (Terraform) and CI/CD for data platforms
- Hands-on use of AI tools in your own engineering workflow - for code, testing, documentation or pipeline build - and a view on where they help and where they don't
- Opinions on partitioning, cluster sizing and warehouse cost - and the results to back them up
- Experience leading or influencing technical direction on large programs, whether through a title or through being the person everyone asks
- Comfort in front of clients - explaining tradeoffs to technical and non-technical stakeholders, and keeping delivery on track
Databricks, Snowflake or AWS certifications will strengthen your application. Azure experience is welcome, but this role leans AWS.
Interested?
Apply here, or connect with me on LinkedIn and send your CV through: https://www.linkedin.com/in/jasonpretorius/
Our client can only consider Australian citizens or permanent residents for these roles.