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Xero

GM/VP Data Engineering

LocationAU: Sydney (45 Clarence St)
Work modehybrid
Typefull-time
DepartmentData, AI & Machine Learning
Company size5,001–10,000 people
First seen1w ago
Last seen3d ago
Our Purpose
At Xero, we’re here to make life better for people in small business, their advisors and communities around the world. By making small businesses more efficient every day, connecting them with big business technology and empowering a community behind them, their potential is limitless. When that happens, we’re not only helping small businesses, we’ll be building a stronger economy that can change the world.
How you’ll make an impact
As GM of Data Engineering, you will lead Xero’s shared data engineering function to turn Xero-wide data strategy into an executable operating model, a coherent platform strategy, and a disciplined sequence of bets across self-service, governance, agentic capability and platform reliability .
You and your team will be at the forefront of Xero’s internal AI transformation, providing agentic-first data platforms, core data products, engineering patterns, governance-by-design controls, and specialist delivery capability that let Xero use data safely, reliably and at scale. You will act as a visible enterprise leader, removing barriers to collaboration across Xero, lifting capability through other leaders, and shaping a trusted, reliable and economically sound data platform environment that supports trusted analytics, self-service, and AI experiences.
What you’ll do
Strategy & Business Impact
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Lead the execution of Data Engineering strategy so Xero’s shared platforms enable trusted analytics, self-service and agentic capability across the organisation. Translate strategy into clear operating rhythms, ownership boundaries, roadmaps and measurable priorities across platform reliability, governance, enablement and simplification.
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Partner with functional data and analytics teams so they increasingly own domain outcomes, while Data Engineering provides platform capability, ingestion, modelling patterns, shared products and guardrails where needed.
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Guide the function through significant organisational, strategic and technical ambiguity, making principled trade-offs that balance reliability, pace, customer value, compliance and commercial outcomes. Align platform, commercial and delivery decisions with Xero’s broader business priorities, including cost discipline, vendor value, and long-term platform economics.
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Maintain a strong grip on operational health by ensuring critical platforms have clear runbooks, dashboards, escalation paths, ownership, health reviews and measurable service expectations.
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Lead and grow a strong leadership bench across Data Engineering and build the capabilities needed for current and future ambitions through team design, recruitment, succession planning, coaching and cross-functional collaboration.
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Create clarity for leaders and teams by setting clear expectations, improving prioritisation, and reducing single-threaded dependence on a small number of individuals. Champion a high-performance, high-trust culture that values engineering quality, operational discipline, continuous improvement, and thoughtful development pathways.
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Build strong working relationships with leaders across Xero, removing barriers to collaboration and influencing outcomes well beyond your immediate reporting line.
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Lead data discussions in senior forums, operating-model conversations and cross-functional planning, bringing balanced judgement, context and data to difficult decisions.
Success looks like
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Data Engineering has clear ownership boundaries and is a trusted collaborator for all things data, platform stewardship, engineering quality and delivery against the outcomes that matter most.
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Agentic insights and self-service capabilities scale in a way that is operationally credible, secure and useful, rather than fragmented or experimental for too long.
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Xero’s data landscape becomes simpler over time through standardised ingestion, better observability, legacy decommissioning and clearer platform choices. Shared data platforms are reliable, observable, secure and economically sustainable, with fewer fragile dependencies and better operational discipline.
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Functional data and analytics teams increasingly own their domain outcomes, with Data Engineering enabling them through reusable platforms, patterns and guardrails rather than acting as a bottleneck. Governance is embedded into platform behaviour and workflows, reducing manual effort, ambiguity and risk.
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The function scales through strong leaders and reduced single-threading, with better succession depth and clearer execution ownership.
What you’ll bring with you
Critical competencies
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Proven experience leading medium to large engineering organisations and delivering results against strategic objectives over a 1–2 year horizon.
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Strong strategic and operating-model judgement, with the ability to turn broad company priorities into executable plans, trade-offs and sequencing.
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Deep experience in data engineering, platform engineering, or adjacent technical leadership domains, with enough technical fluency to assess architecture, delivery, operational and commercial implications when needed.
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Demonstrated ability to lead through ambiguity, simplify cross-functional problems and create momentum across multiple stakeholders and teams.
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Strong communication and influence skills, including executive-level communication, crisp narrative writing, and the ability to gain commitment around difficult or unpopular ideas.
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A track record of building strong teams, developing leaders, identifying successors, and improving processes, systems and ways of working at organisational scale.
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Strong business acumen, including the ability to connect technical investments to customer value, business priorities, market context and financial outcomes.
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Sound judgement in balancing long-term platform health, governance and reliability with pace, customer impact and commercial reality.
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