About the role:
A player-coach role: build the hardest things, and grow the people building the rest.

As a Data Engineering Lead you are accountable for what your team builds and whether it works. You will spend roughly 80% of your time doing the engineering and 20% leading, and both halves are the job.

You will hold the technical standard of a Principal Data Engineer, take the hardest work on the team, and lift direct reports whose growth you own. We are explicit that this role stays hands-on. If it stops being hands-on, something has gone wrong and we will fix it rather than quietly redefine the role.

This is the right role for a senior or principal data engineer who wants to lead without stepping away from building. Reporting to the GM Data and AI Enablement, this role manages a team of Data Engineers. Some of your team will be aligned to Platform outcomes, others may be embedded into Missions delivering outcomes.

What you will do

- Design and build the platform the team runs on: ingestion, orchestration, integration patterns and the deployment path, without becoming the bottleneck, and deliberately delegating problems so your team grows.
- Build and run the platform behind LMG's corporate machine learning and generative AI: deployment and serving, model registry, retrieval and vector infrastructure, monitoring, retraining and guardrails. Data Engineering owns this runtime. Software Engineering owns anything customer-facing, and you own the handover when a solution crosses that line.
- Set technical direction for your team's data domain,



hold the definition of done, and make trade-offs explicit rather than implicit.
- Partner with Technology, set standards, runbooks and playbooks: the quality bar, how work gets reviewed, how a system is recovered, how an incident is handled, and how governance, consent, retention and audit obligations are met.
- Turn ambiguous business direction into a sequenced plan the team can deliver, and communicate changes early with their cost.
- Run one-to-ones, own growth plans, give feedback close to the event, and write and deliver performance reviews.
- Be accountable for service levels, issue response, run cost and technical debt, systems failing safely and visibly, and keep the team's operational load sustainable and within working hours.
- Own the technical hiring loop for your team and own recent starters' first ninety days.

What you will bring

- The technical depth to be the strongest engineer in the room without needing to be.
- Experience growing engineers, including the tough conversations.
- Deep hands-on experience building and running cloud data platforms; ingestion, orchestration, transformation and the deployment path.
- Experience putting machine learning or generative AI into production, or the platform depth and appetite to own it.
- A track record of delivering through other people as well as through your own work.
- The judgement to know which problems to take yourself and which to hand away.
- The instinct to notice when someone on your team is struggling before they say so.

📌 Data Engineering Lead (Melbourne)
🏢 Ray White
📍 Melbourne