Data Engineer - Data Platforms - Snowflake

Whizdom; Sydney; Hybrid; AUD 120,000 - 150,000; Full time

Benefits offered by this job

Hybrid working environment

Job summary

Whizdom in Sydney is seeking a hands-on Data Engineer to join its data platforms team on a 6+ month contract. You will lead Snowflake migrations, build scalable data pipelines with dbt and Airflow, and leverage AI tooling like GitHub Copilot and Cortex AI to speed development.

Key responsibilities include end-to-end migration design, Snowflake optimisation, SQL/PLSQL proficiency, and implementing CI/CD, data quality checks, and production support in a hybrid cloud environment.

Qualifications

• Strong experience in SQL and PL/SQL.
• Hands-on Snowflake migrations and data engineering.
• Proficiency with dbt and Airflow for data pipelines.
• Python scripting for automation and utilities.
• Experience with Cortex AI or similar AI-assisted development.

Responsibilities

• Design end-to-end Snowflake migrations from on-prem to Snowflake.
• Develop and optimise Snowflake data models and pipelines.
• Build dbt models, tests, snapshots and transformations.
• Create and manage Airflow DAGs for data orchestration.
• Leverage GitHub Copilot and Cortex AI to accelerate development.
• Implement data quality checks, CI/CD, and production support.

Skills

SQL

Snowflake Migration

Snowflake

dbt

Apache Airflow

Python

GitHub Copilot

Snowflake Cortex AI

Tools

Airflow

Snowflake

Python

Job description

Data Engineer - Data Platforms - Snowflake

• Sydney (preferred), Other locations considered
• Hybrid Working Environment
• 6 + month contract

About the Role

We're partnering with a leading organisation seeking a Data Platform Engineer to join a growing data and analytics team.

We are looking for a hands-on Data Engineer with strong expertise in Snowflake migration and data engineering. You should be capable of delivering end-to-end data migration solutions, building scalable data pipelines using dbt and Apache Airflow, and leveraging GitHub Copilot and Snowflake Cortex AI to accelerate development and enable AI-driven solutions.

What You'll Be Doing

• Snowflake Migration: Design and implement end-to-end migration solutions from any legacy on-premises platforms, e.g. SAS, Netezza, Teradata, etc., to Snowflake. Develop reusable migration frameworks and Python automation scripts.
• Snowflake Engineering: Develop and optimise Snowflake SQL, data models, ingestion pipelines, and transformation workflows. Apply performance-tuning and cost-optimisation best practices.
• SQL: Strong experience in writing SQL and PL/SQL queries.
• dbt Development: Build and maintain dbt models, macros, tests, snapshots, and incremental transformations integrated with Snowflake.
• Workflow Orchestration: Develop and manage Apache Airflow DAGs for scheduling and orchestrating data pipelines, including monitoring, dependency management, retries, and error handling.
• AI-Assisted Development: Use GitHub Copilot for code generation, refactoring, debugging, test creation, and documentation, ensuring code quality and security.
• Snowflake Cortex AI: Implement or integrate Cortex AI capabilities for use cases such as text processing, information extraction, semantic search, and natural-language analytics.
• Quality and Delivery: Implement data quality checks, automated testing, reconciliation, version control, CI/CD, and production support practices.

What You'll Bring

1. SQL: Strong experience in writing SQL and PL/SQL queries.
2. Snowflake Migration: Proven hands-on experience delivering end-to-end migrations, including framework development, automation, data validation, and reconciliation.
3. Snowflake: Strong SQL, data modelling, pipeline development, and performance optimisation skills.
4. dbt: Practical experience developing models, macros, tests, and incremental transformations.
5. Apache Airflow: Hands-on experience building DAGs and managing pipeline orchestration.
6. Python: Experience developing migration utilities, automation scripts, and data validation solutions.
7. GitHub Copilot: Practical usage for AI-assisted coding and engineering productivity.
8. Snowflake Cortex AI: Practical implementation experience or demonstrable project-level expertise in Cortex AI capabilities.

Why Apply?

• Opportunity to work with modern cloud data technologies
• Supportive team environment with experienced engineers and technical leaders
• Exposure to enterprise-scale data platforms and automation initiatives
• Flexible and hybrid working arrangements

Candidates will need to be willing to undergo pre-employment screening checks which may include, ID and work rights, security clearance verification and any other client requested checks.