Senior Analytics Engineer - AI-Ready Data & BI

Tribe Group; Auckland; Hybrid; NZD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid working

Competitive salary and benefits

Collaboration with data leadership

Job summary

Tribe Group is seeking an Analytics Engineer to own curated datasets, semantic models and the reporting layers relied upon by the business. You will work across Microsoft Fabric, Databricks and Power BI to deliver trusted analytics products and partner closely with stakeholders to translate operational needs into robust solutions.

You will contribute to emerging AI-enabled capabilities, including AI-ready data assets and research/agent workflows, while maintaining solid engineering practices and

Qualifications

• Proven SQL and analytics engineering experience.
• Experience building semantic models and governed metrics for BI.
• Experience with Microsoft Fabric and/or Databricks (lakehouse/warehouse patterns, pipelines, notebooks).
• Ability to translate operational needs into robust analytics solutions.
• Strong Git, testing/validation, documentation, and DataOps-style delivery habits.

Responsibilities

• Own curated datasets, semantic models and reporting layers.
• Deliver trusted analytics products across Power BI, Fabric and Databricks.
• Partner with stakeholders to translate business needs into robust solutions.
• Contribute to AI-enabled analytics capabilities and data assets.

Skills

SQL

Analytics engineering

Power BI

Databricks

Microsoft Fabric

Git

Testing/validation

DataOps

Stakeholder collaboration

Tools

Notebooks

Job description

Tribe Group is seeking an Analytics Engineer to own curated datasets, semantic models and the reporting layers relied upon by the business. You will work across Microsoft Fabric, Databricks and Power BI to deliver trusted analytics products and partner closely with stakeholders to translate operational needs into robust solutions.

You will contribute to emerging AI-enabled capabilities, including AI-ready data assets and research/agent workflows, while maintaining solid engineering practices and