Data Analytics Engineer — AI-Driven Pipelines (Hybrid)

IAG; Christchurch; Hybrid; NZD 100,000 - 170,000; Full time

Benefits offered by this job

13% superannuation

20 days leave + 5 MyLeave

MyFlex work options

Insurance discounts

Partner discounts on health, tech &amp

Parental leave 20 weeks

LinkedIn Learning & IAG Academy

Study assistance & secondments

Job summary

IAG is hiring a data/analytics engineer to monitor data pipelines, optimise data models, and investigate quality issues. The role involves managing releases, communicating progress to stakeholders, and documenting technical procedures.

You will work in a flexible hybrid setup with access to extensive learning resources and insurance-related benefits. The ideal candidate has 2-5 years in data engineering, strong SQL/Python/DBT skills, and hands-on experience with BigQuery and GCP.

Qualifications

• 2-5 years in data engineering or analytics engineering with a strong software development background.
• Proficient in SQL, Python, DBT; BigQuery and Google Cloud Platform essential.
• Experience implementing AI-driven data testing, optimisation, and governance tools.
• Familiar with Agile methodologies and DevOps, including CI/CD and Git.

Responsibilities

• Monitor data pipelines and data products to ensure accurate, timely data for business users.
• Optimise data models and pipeline orchestration to boost efficiency, reliability, and performance.
• Investigate data quality issues, identify root causes, and implement sustainable fixes.
• Manage releases and deployments across higher environments with proper governance.
• Communicate release activities, risks, and outcomes to stakeholders with timely updates.
• Create and maintain technical, operational, and support documentation for smooth BAU handover.

Skills

SQL

Python

DBT

BigQuery

Google Cloud Platform

AI data testing

Agile & DevOps

Data governance

Tools

Git

CI/CD pipelines

Job description

IAG is hiring a data/analytics engineer to monitor data pipelines, optimise data models, and investigate quality issues. The role involves managing releases, communicating progress to stakeholders, and documenting technical procedures.

You will work in a flexible hybrid setup with access to extensive learning resources and insurance-related benefits. The ideal candidate has 2-5 years in data engineering, strong SQL/Python/DBT skills, and hands-on experience with BigQuery and GCP.