Facilities Data & Asset Analyst

Auckland Council; Auckland; On-site; NZD 70,000 - 90,000; Full time

Benefits offered by this job

EAP services

Oranga Day

discounted Leisure Centre membership

range of other partnership discounts

flexible working options

Job summary

Auckland Council is seeking a Facilities Analyst to join the Property Portfolio team in Auckland City. This full-time, on-site role focuses on data-driven facilities and asset management decisions, delivering robust reporting and insights to support operational and strategic planning.

You'll manage data across SAP, GIS and related systems, engage with stakeholders, and drive process improvements to enhance data quality and efficiency.

Qualifications

• 2-3 years’ experience within a property related environment.
• Systems experience working with SAP RE and PM modules.
• Intermediate level (or higher) Excel & Power BI skills.
• Demonstratable experience of analytical skills & data management.
• An understanding of Geospatial systems.

Responsibilities

• Maintaining and improving facilities, asset and property data across SAP, GIS and related systems
• Delivering meaningful reporting and analysis to support operational, financial and strategic decision-making
• Identifying opportunities for process improvements and driving initiatives that enhance efficiency and data quality
• Providing systems guidance and training to users across the business
• Building strong relationships with internal stakeholders and acting as a trusted source of information and insights

Skills

Data analysis

Power BI

Excel

Stakeholder engagement

Geospatial systems

Tools

SAP RE

PM modules

Job description

Auckland Council is seeking a Facilities Analyst to join the Property Portfolio team in Auckland City. This full-time, on-site role focuses on data-driven facilities and asset management decisions, delivering robust reporting and insights to support operational and strategic planning.

You'll manage data across SAP, GIS and related systems, engage with stakeholders, and drive process improvements to enhance data quality and efficiency.