Data Platform Product Lead

Wastemanagement8; Auckland; On-site; NZD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive salary

Career path

Work-life balance initiatives

Professional development

Onsite cafe and carpark

Discounts on products for you and your

Discounts on fuel

Job summary

WM in Auckland is seeking an experienced Data Platform Lead to own the vision for our data products, blending hands-on analytics engineering with clear product strategy and stakeholder coordination.

You will shape the roadmap for curated datasets, metrics layers and analytical models, work with Snowflake and dbt, mentor engineers, and drive delivery through agile ceremonies and strong collaboration with the data engineering team.

Qualifications

• Experience owning a backlog and shipping data products.
• Strong SQL skills and data modelling knowledge.
• Hands-on analytics engineering with product ownership.
• Experience with dbt, Snowflake and cloud data warehouses.
• Ability to lead discovery sessions with stakeholders.
• Mentoring and coaching engineers on product thinking.

Responsibilities

• Own the product vision and roadmap for data products.
• Build data products hands-on using dbt and Snowflake.
• Manage the product backlog and translate business needs into specs.
• Lead day-to-day delivery and unblock issues.
• Drive stakeholder relationships and manage expectations on timelines.
• Mentor engineers to enhance product thinking and business context.

Skills

Product ownership

Stakeholder management

Mentoring

Analytics engineering

SQL

Tools

dbt

Snowflake

Git workflows

CI/CD

Job description

WM in Auckland is seeking an experienced Data Platform Lead to own the vision for our data products, blending hands-on analytics engineering with clear product strategy and stakeholder coordination.

You will shape the roadmap for curated datasets, metrics layers and analytical models, work with Snowflake and dbt, mentor engineers, and drive delivery through agile ceremonies and strong collaboration with the data engineering team.