Looking for an engineer who wants to own the transformation layer, not just feed it. This role is about building and maintaining the dbt models and pipelines that turn raw data into clean, trusted, production-grade datasets - with Snowflake as the platform and dbt as the daily tool of choice.
You'll work across the full lifecycle of the transformation layer: designing modular dbt models, writing tests that catch problems before they reach anyone downstream, and diagnosing issues when something breaks - a failed job, a data-quality defect, a model running slower than it should. It's hands‐on engineering work with real ownership, not ticket‐based maintenance.
Responsibilities will include:
Designing, developing and maintaining modular dbt models across the data layer
Implementing automated data-quality tests, model and column documentation, lineage and source-freshness controls
Diagnosing and resolving failed dbt jobs, data-quality defects and model-performance issues
Developing reusable transformation patterns and business logic that can support multiple downstream use cases
Optimising Snowflake queries and dbt models for performance and cost efficiency
Participating in pull requests, code review and CI/CD processes
Contributing to standards, frameworks and best practices for analytics engineering
Looking for an engineer who wants to own the transformation layer, not just feed it. This role is about building and maintaining the dbt models and pipelines that turn raw data into clean, trusted, production‐grade datasets - with Snowflake as the platform and dbt as the daily tool of choice.




You'll work across the full lifecycle of the transformation layer: designing modular dbt models, writing tests that catch problems before they reach anyone downstream, and diagnosing issues when something breaks - a failed job, a data-quality defect, a model running slower than it should. It's hands‐on engineering work with real ownership, not ticket‐based maintenance.
Responsibilities will include:
Designing, developing and maintaining modular dbt models across the data layer
Implementing automated data-quality tests, model and column documentation, lineage and source-freshness controls
Diagnosing and resolving failed dbt jobs, data-quality defects and model-performance issues
Developing reusable transformation patterns and business logic that can support multiple downstream use cases
Optimising Snowflake queries and dbt models for performance and cost efficiency
Participating in pull requests, code review and CI/CD processes
Contributing to standards, frameworks and best practices for analytics engineering
Skills we are looking for:
Advanced SQL and dimensional modelling
Extensive and hands‐on production experience with dbt (non‐negotiable, not just exposure)
Experience with Snowflake or a comparable cloud data warehouse
Git‐based development, code review, automated testing and CI/CD practices
Proven ability to diagnose and resolve data pipeline and transformation issues
Comfort working independently on defined areas of the data stack, escalating complex architectural decisions where needed
Excellent communication & stakeholder management skills
#J-*****-Ljbffr

📌 Analytics Engineer (Dbt/Data Engineering) (Melbourne)
🏢 iterate
📍 Melbourne