Want to be a part of Asia Pacific & Middle East's (APME) largest, most innovative, and rapidly growing data centre company?
AirTrunk is a hyperscale data centre company with a powerful purpose - to scale and sustain the relentless growth of the region’s digital future. We do this by continuously redefining and delivering the digital infrastructure that meet the needs of our customers - the world’s most transformational companies. And we’re doing so sustainably, for today and tomorrow.
Having opened Australia’s first and largest hyperscale data centres in 2017, we set our eyes on rapid expansion and now operate a platform of hyperscale data centres across the APME region. With backing from our investors, including Blackstone, this is just the beginning…
Come join the A-Team at AirTrunk, where the cloud meets the ground.
Your Impact
The AI & Data Management Lead is a senior, strategic role responsible for establishing and scaling enterprise-wide data and AI management capabilities from the ground up. Reporting to the Senior Director – AI, Automation & Data Insights, this position plays a pivotal role in shaping how the organisation governs, protects, and leverages data and AI systems.
You will lead the design and delivery of a foundational enterprise data & AI governance framework, ensuring the organisation operates with trust, safety, and compliance as its AI and data usage accelerates. This includes building standards, policies, controls, and operating models that uplift literacy and embed responsible use across the organisation.
As one of the most senior data & AI leaders, you will deeply influence strategy, champion maturity uplift, and collaborate with business and technology teams to embed world‑class governance, quality, and management practices. Initially an individual contributor, this role will leverage consultant capacity and may grow into a formal team over time.
What You'll Do
Strategic Leadership
- Partner with the Senior Director - AI, Automation & Data Insights to set the organisation’s AI & Data Management strategy and multi‑year roadmap, ensuring strong alignment to business, regulatory, and transformation priorities.
- Build the organisation’s enterprise data governance framework from the ground up, embedding global data‑management standards such as DAMA‑DMBoK or relevant ISO standards, while ensuring alignment with relevant local government data guidance in the regions AirTrunk operates in.
- Develop and own the organisation’s Responsible AI framework aligned to modern AI system standards, relevant ISO standards and emerging Australian government AI safety and regulatory guidance. Define the policies, controls, and lifecycle governance required for safe and compliant AI system deployment.
- Develop a multi‑year approach to progressively bring critical business processes, data domains, and AI‑enabled systems under governance. Provide strategic advisory to executives on risk, compliance, ethics, and maturity uplift.
Governance, Frameworks & Compliance
- Build and operationalise the enterprise data governance framework, including standards for data quality, metadata, lineage, classification, access, retention, and stewardship.
- Define how AI systems are assessed, approved, monitored, and maintained, including model risk management and system lifecycle governance.
- Establish processes for evaluating and approving AI use cases, including third‑party and embedded AI capabilities within enterprise systems.
- Ensure alignment across Legal, Risk, Cybersecurity, Enterprise Architecture, and Technology to maintain a unified governance posture.
- Develop and maintain the policies, guidelines, and assurance processes that underpin safe and compliant data & AI operations.
Data & AI Architecture, Enablement & Operations
- Establish architecture patterns and operational standards that ensure data quality, trustworthy analytics, and safe AI system deployment.
- Partner with data and AI platform teams to embed governance requirements into tooling and workflows (catalogues, metadata, lineage, quality monitors, approval flows).
- Lead the design of data ownership models, data contracts, and master/reference data approaches.
- Define oversight for model and AI system documentation, versioning, deployment safeguards, and auditability.
- Evaluate the technology ecosystem required to support enterprise data management and AI governance, ensuring scalability and future readiness.
Delivery & Execution
- Stand up the foundational operating model for data and AI governance, including stewardship networks, governance councils, approval workflows, and risk controls.
- Lead key initiatives to implement governance across the data and AI lifecycle from ingestion to deployment and monitoring.
- Manage consultants and delivery partners to accelerate capability build-out where needed.
- Establish metrics, KPIs, and maturity measures to track progress and demonstrate impact.
- Ensure governance processes are embedded sustainably within business and technology operations.
Capability, Culture & Literacy
- Build and deliver enterprise data and AI literacy programs, ensuring employees understand their responsibilities, risks, and best practices.
- Provide targeted training for executives, data stewards, system owners, and AI practitioners.
- Act as a trusted advisor to business units, helping them adopt governance practices, uplift maturity, and reduce operational and AI‑related risk.
- Foster a culture of responsible, ethical, and high‑quality AI and data use across the organisation.
- Drive awareness, communication, and engagement activities that make governance clear, accessible, and business‑aligned.
What You'll Bring
- 10+ years’ experience in data governance, data management, or AI governance leadership roles.
- Proven experience designing and implementing enterprise‑grade data governance or AI governance frameworks.
- Strong understanding of global and Australian AI governance standards, privacy regulations, and emerging regulatory trends.
- Experience developing policies, standards, controls, and operating models at scale.
- Familiarity with AI/ML lifecycle management, model risk, data quality frameworks, metadata and cataloguing technologies, and governance tooling.
- Ability to influence senior stakeholders, translate technical concepts for executive audiences, and drive enterprise adoption.
- Demonstrated experience uplifting organisational literacy in data, analytics, or AI.
- Strong communication, negotiation, and facilitation skills