Data Platform Lead — AI‑Ready & Cloud‑Driven

Bank of New Zealand

Auckland

Hybrid

NZD 150,000 - 210,000

Full time

13 days ago

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Job summary

Bank of New Zealand is seeking an experienced Platform Lead to guide a high-performing data team and maximise the value of our Master Data Hub. You’ll shape the data lifecycle from ingestion to governed assets, reporting and analytics, including AI use cases.

The role is full-time and permanent, based in Auckland or Wellington with a hybrid pattern (three days in the office, two flexible). You’ll partner with data practitioners and business customers to deliver trusted data assets.

Qualifications

Platform Lead or similar experience across data platforms.
Proven people leadership across recruitment, onboarding, development, performance and engagement.
Knowledge of modern data and engineering practices including ingestion, transformation, orchestration, cloud data services and DevOps.
Knowledge of trusted data assets and controls including quality, metadata, lineage, classification, security, access and lifecycle management.
Ability to use data, KPIs, platform health and customer insights to guide prioritisation and investment.
Strong stakeholder management and communication across data, technology, governance and non-technical audiences.
Experience with modern data technologies and cloud platforms would help, such as Snowflake, dbt, Fivetran, Airflow or similar.
Experience in banking or financial services, and a relevant business or technology qualification, would be beneficial.

Responsibilities

Define data platform vision, strategy and roadmap aligned with BNZ priorities, data strategy and customer needs.
Lead, support and develop a team of engineers and technical specialists, creating a culture of trust, collaboration and accountability.
Own and prioritise the backlog, balancing customer value, business impact, data asset enablement, risk, operational hygiene and available resources.
Support the delivery of secure, trusted and reusable data assets by embedding appropriate standards for data quality, metadata, lineage, classification, access and lifecycle management.
Use customer insights, data and performance metrics to guide decisions and continuously improve platform reliability, usability, cost efficiency and value.
Own service performance, stability and continuous improvement, including proactive monitoring, incident response, post-incident reviews and actions that improve resilience, data availability and recoverability.