Data Engineer - Data Platforms - Snowflake
Summary
A 6+ month contract Data Platform Engineer role in Sydney (hybrid, other locations considered) via Whizdom for a leading organisation. Day to day: migrate legacy platforms (SAS, Netezza, Teradata) to Snowflake, build dbt models and Airflow pipelines, and use GitHub Copilot and Snowflake Cortex AI to accelerate and enhance data engineering.
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
- SQL: Strong experience in writing SQL and PL/SQL queries.
- Snowflake Migration: Proven hands-on experience delivering end-to-end migrations, including framework development, automation, data validation, and reconciliation.
- Snowflake: Strong SQL, data modelling, pipeline development, and performance optimisation skills.
- dbt: Practical experience developing models, macros, tests, and incremental transformations.
- Apache Airflow: Hands-on experience building DAGs and managing pipeline orchestration.
- Python: Experience developing migration utilities, automation scripts, and data validation solutions.
- GitHub Copilot: Practical usage for AI-assisted coding and engineering productivity.
- 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.