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About the Role

The Head of Data Engineering leads the consolidated Data Engineering capability across IT and the former Data and Analytics Centre of Excellence. The role is accountable for the design, build, operation and continuous improvement of enterprise data engineering and machine learning engineering capabilities. The role brings foundational and derived data engineering into one integrated function, creating trusted, reusable and ready-to-consume data products that support operational workloads, reporting, analytics, data science and AI delivery.

Responsibilities

Lead and develop the consolidated Data Engineering function, bringing together IT BAU engineering and former CoE data and ML engineering capability under clear accountabilities and ways of working.
Build a collaborative, high-performing team capable of delivering and operating enterprise-scale data products, pipelines and engineering services.
Establish effective interfaces with Data Analytics & Reporting, AI Delivery, Architecture, Data Governance & AI Mobilisation and Technology Operations.
Develop workforce, sourcing, succession and capability plans aligned to the future data platform roadmap and delivery portfolio.
Develop and maintain the enterprise Data Engineering strategy, roadmap and operating model in alignment with the Data Platforms & AI Delivery strategy.
Consolidate data engineering standards, practices, tooling and governance across previously separate IT and CoE teams.
Define how foundational, curated and derived data products are created, owned, operated and consumed across the organisation.
Prioritise engineering capacity across BAU, regulatory, transformation, analytics and AI demand using transparent portfolio and capacity management practices.
Lead the design, build and operation of reliable, secure and scalable cloud-based data pipelines, ELT/ETL solutions and data products.
Ensure foundational data products are transformed into trusted, reusable and ready-to-consume datasets that support a consistent source of truth.
Establish engineering standards for data ingestion, transformation, modelling, orchestration, metadata, lineage, observability and release management.
Ensure data products meet agreed quality, availability, performance, security, resilience and support requirements.
Manage the lifecycle of data engineering assets, including technical debt, optimisation, remediation and decommissioning.
Lead ML engineering capability required to industrialise, deploy, monitor and optimise approved machine learning and AI solutions.
Partner with Data Analytics & Reporting and AI Delivery teams to move validated prototypes and use cases into scalable production services.
Establish repeatable MLOps and engineering practices covering deployment, monitoring, model performance, versioning and operational support.
Ensure AI and ML engineering solutions comply with architecture, security, privacy, data governance and responsible AI requirements.
Own a portfolio of ongoing and project-based data engineering work, with clear outcomes, milestones, dependencies, risks and resource requirements.
Ensure engineering services transition into sustainable operational ownership with clear support models, service expectations and controls.
Establish meaningful measures for delivery performance, platform reliability, data quality, engineering productivity and customer outcomes.
Use performance, incident and stakeholder insights to drive continuous improvement and prioritise remediation.
Manage budgets, suppliers, delivery partners and commercial commitments within agreed constraints.
Partner with Data Governance & AI Mobilisation to embed data ownership, quality, metadata, lineage, access and retention requirements into engineering practices.
Build trusted relationships with business and Technology stakeholders and translate data needs into practical engineering priorities and solutions.
Ensure material delivery, operational, security, privacy, data quality and technology risks are identified, controlled and appropriately escalated.
Provide clear reporting and advice to senior leaders on engineering performance, investment needs, risks and decisions required.

Requirements

Tertiary qualifications in Computer Science, Data Engineering, Software Engineering, Information Technology, Mathematics or a related quantitative discipline, or equivalent relevant experience.
Relevant cloud, data engineering, data architecture, data management or machine learning engineering certifications would be highly regarded.
Significant experience leading enterprise data engineering, platform engineering or ML engineering functions in a large and complex organisation.
Demonstrated experience consolidating teams, practices or platforms and establishing an effective enterprise data engineering operating model.
Extensive experience developing, deploying and operating cloud-based data platforms, pipelines and ELT/ETL solutions.
Experience creating reusable foundational and derived data products across structured and unstructured data environments.
Experience establishing data modelling, data quality, metadata, lineage, observability, DevOps and MLOps practices.
Demonstrated experience managing a portfolio of BAU and project delivery, including budgets, capacity, dependencies, risks and suppliers.
Proven people leadership experience, including building and sustaining high-performing technical teams through organisational change.
Experience influencing senior business and technical stakeholders and delivering outcomes across organisational boundaries.
Strong knowledge of modern cloud data platforms, data integration, distributed processing, data modelling and data product principles.
Strong understanding of software and data engineering practices, including CI/CD, automated testing, infrastructure as code, observability and operational support.
Working knowledge of machine learning engineering and MLOps practices required to deploy and operate models and AI services at scale.
Strong understanding of data governance, privacy, security, quality, metadata and responsible AI requirements.
Strong commercial, portfolio and delivery management capability.
Highly developed leadership, communication, stakeholder engagement and influencing skills.
Ability to translate complex technical information into clear recommendations, priorities and decisions.

Skills

Data Engineering
Machine Learning Engineering
Cloud-based data platforms
Data pipelines
ELT/ETL solutions
Data products
Data ingestion
Data transformation
Data modelling
Orchestration
Metadata management
Lineage tracking
Observability
Release management
MLOps
DevOps
CI/CD
Automated testing
Infrastructure as code
Data governance
Data quality
Data security
Data privacy
Responsible AI
Portfolio management
Capacity management
Stakeholder management
Commercial management
Delivery management
Leadership
Communication
Influencing skills

Location

Barangaroo

Work Type

Hybrid
Full-time

Experience Level

Head of Data Engineering
Senior
Leadership

Education Level

Tertiary qualifications in Computer Science, Data Engineering, Software Engineering, Information Technology, Mathematics or a related quantitative discipline, or equivalent relevant experience.
Cloud, data engineering, data architecture, data management or machine learning engineering certifications

Benefits

Flexible hybrid way of working (from home and office)
‘Stay Connected Mobile’ – Access to a free mobile plan
‘Stay Connected NBN’ – Access to a free, high‑speed NBN plan (up to 500 Mbps)
‘Your Leave’ - additional leave to be used whenever you like - every year
Access to TPG Learning Hub platform and internal development opportunities
Access to Corporate Partner Discounts

About the Company

TPG Telecom started with a belief that we can make things better for Australians. We believe in the power of meaningful relationships to support vibrant, connected communities where everyone belongs. It’s our why; our reason to exist. Now, we’re proud to be one of Australia’s leading mobile and internet providers. We’re not just redefining telco, we’re changing its course. And you play a role in that. A big one. The opportunities are plenty for those who are ready to accept the challenge.
Our Technology team builds and evolves the networks and platforms that keep millions of Australians connected every day. From mobile and fixed networks to digital platforms and data, you’ll work at the forefront of innovation solving complex challenges and helping shape the future of connectivity.

Equal Opportunity

Don’t meet every single requirement? That’s OK! At TPG Telecom, we’re all about creating an accessible workplace where everybody feels safe to bring their authentic self to work - regardless of background. If you think this role is a great fit for you but some of the qualifications don’t align with your experience, we still encourage you to apply - you might just be the perfect candidate for a similar role with us! Learn more about life at TPG Telecom here.
TPG Telecom also acknowledges the Gadigal People of the Eora Nation as the Traditional Custodians of lands and waterways where this office can be found in Barangaroo.