Flexible Data Engineer: AI Pipelines & Platform

The GPT Group; Sydney; Hybrid; AUD 130,000 - 170,000; Full time

Benefits offered by this job

Flexible working

Parental leave 22 weeks

Learning & Development

Wellbeing programs

Employee Referral Program

Job summary

The GPT Group is seeking a hands-on Data Engineer to join our Data & Analytics team in Sydney. You will design, build and maintain ingestion pipelines, databases and datasets that power our data platform and AI estate.

This is a build-and-run role with day-to-day operations and collaboration with external data and AI partners. You’ll work under the Data Engineering Manager, use AI-assisted tooling to accelerate delivery, and contribute to data products, analytics engineering, and the semantic

Qualifications

• Ter tiary educated data engineer with production pipelines experience.
• Exposure to modern analytics tooling and AI/GenAI data workflows is a plus.
• Strong SQL, Python and cloud data warehouse knowledge required.

Responsibilities

• Build and maintain data ingestion pipelines across structured and unstructured sources.
• Develop and maintain components of the data platform (Snowflake, databases, tooling).
• Support platform reliability, performance and cost by monitoring pipelines and resolving issues.
• Contribute to analytics engineering and semantic layer with curated datasets for reports and products.
• Create AI-facing data foundations to support AI team data products.
• Follow engineering standards and code review practices.

Skills

SQL

Python

Snowflake

dbt

Education

Tertiary degree

Tools

Snowflake

dbt

Job description

The GPT Group is seeking a hands-on Data Engineer to join our Data & Analytics team in Sydney. You will design, build and maintain ingestion pipelines, databases and datasets that power our data platform and AI estate.

This is a build-and-run role with day-to-day operations and collaboration with external data and AI partners. You’ll work under the Data Engineering Manager, use AI-assisted tooling to accelerate delivery, and contribute to data products, analytics engineering, and the semantic