Data Engineering Lead

Posted 26 Days Ago
Be an Early Applicant
Hiring Remotely in QLD, AUS
Remote
Senior level
Real Estate • Financial Services • PropTech
Australia’s leading real estate brand.
The Role
Lead a hands-on data engineering team while building and operating cloud data platforms, ingestion and orchestration systems, deployment paths, and machine learning and generative AI infrastructure. Set technical standards, ensure reliability and governance, manage technical debt and operational costs, develop engineers, conduct performance reviews, lead hiring, and oversee onboarding. The role spends approximately 80% of its time on engineering and 20% on people leadership.
Summary Generated by Built In

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 new 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.

Skills Required

  • Experience growing engineers, including handling difficult performance or development conversations
  • Deep hands-on experience building and operating cloud data platforms
  • Experience with data ingestion, orchestration, transformation, and deployment paths
  • Experience putting machine learning or generative AI into production, or sufficient platform depth and willingness to own it
  • Track record of delivering outcomes through other people and personal engineering work
  • Technical depth equivalent to a Principal Data Engineer
  • Judgment to prioritize problems and delegate effectively
  • Ability to identify and support struggling team members
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The Company
HQ: Brisbane
9,707 Employees
Year Founded: 1902

What We Do

Ray White is a market-leading real estate agency group and property investment business, operating throughout Australia, New Zealand, Indonesia and Hong Kong. We are a fourth-generation family-owned and led business, founded in 1902 in Crows Nest, Queensland. Our original office - the Shed - in Crows Nest still stands today. There are over 12,000 members of the Ray White family. Our members span all areas of real estate agency activities, including residential, commercial and rural property sales and management. Our specialist businesses focus on specific market sectors such as valuations, marine, and insurance. We are a partner in HTL Property, delivering specialised integrated services for the hotel industry and its investors throughout Australia. RW Capital invests on behalf of the White Family, and institutional and private investors, into private credit, real estate private equity and private equity. We seek to provide all of our members with a family experience that supports leadership, embraces curiosity, and is a springboard for them to reach heights that they might not have thought achievable. We recorded our strongest year of growth and transaction activity in the financial year ending 30 June 2024. Our market share of residential property sales in Australia and New Zealand is at a record high of 14.4%, more than twice the second-largest group.

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