Analytics Engineer (dbt/Data Engineering)

Iterate; Melbourne; On-site; AUD 120,000 - 160,000; Full time

Job summary

Iterate in Melbourne is seeking an engineer to own the transformation layer, building and maintaining 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, and diagnosing issues when something breaks.

Qualifications

• Advanced SQL and dimensional modelling required.
• dbt production experience is non-negotiable.
• 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 decisions when needed.
• Excellent communication and stakeholder management skills.

Responsibilities

• Design, develop and maintain modular dbt models across the data layer.
• Implement automated data-quality tests and lineage controls.
• Diagnose and resolve failed dbt jobs and data-quality defects.
• Develop reusable transformation patterns for multiple downstream use cases.
• Optimize Snowflake queries and dbt models for performance and cost efficiency.
• Participate in PRs, code review and CI/CD processes.
• Contribute to analytics engineering standards and best practices.

Skills

Advanced SQL

Dimensional Modelling

dbt production experience

Snowflake

Git-based development

CI/CD practices

Data quality

Independent work

Stakeholder management

Tools

dbt

Snowflake

Git

Job description

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