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Xero is seeking a Technical Product Manager to lead the modernization of its marketing data platform and drive AI integration across data products. You will operate independently, bridging complex engineering systems and business needs while ensuring foundational architecture supports sophisticated data science and analytics.
Your core responsibilities include:
- Leading the modernization of a 15-year-old data architecture into a modern, scalable ecosystem
- Unifying fragmented data sources to establish a single trusted source of truth
- Collaborating with data engineering and applied science leads to embed AI capabilities into workflows
- Partnering with sales, marketing, and customer support teams to deliver reporting enhancements
- Translating business strategies into actionable requirements for global stakeholders
- Balancing long-term architectural transformation with incremental, high-value product deliveries
You will join a 50-person multidisciplinary team spanning data engineers, data scientists, applied scientists, market insights professionals, and economic researchers across Australia, New Zealand, the UK, and the US. The team manages go-to-market data engineering, science, and research capabilities with a focus on re-evaluating and modernizing the data stack.
The role is ideally based in Melbourne to maintain proximity to the core engineering team, though East Coast Australia applicants are welcome. Xero supports a hybrid model with designated boost days for in-office collaboration.
Requirements:
- Deep technical familiarity with complex, large-scale big data systems and real-time data products
- Proven ability to communicate sophisticated data concepts clearly to senior leadership and non-technical stakeholders
- Experience operating autonomously in ambiguous environments and making confident decisions without clear paths forward
- Skill in managing conflicting priorities from demanding business units (marketing, sales)
- Strong commercial mindset with background in marketing or sales data portfolios
- Comfort partnering with cross-functional engineering and data science teams to assess technical feasibility
