Senior Snowflake Data Engineer - ETL & Pipelines Expert

Charterhouse; Sydney; On-site; AUD 96,000 - 165,000; Full time

Job summary

Charterhouse is seeking an experienced Data Engineer with strong Snowflake expertise to join a growing data and technology team on a contract basis. You will design, build and maintain ETL/ELT pipelines, develop Snowflake data solutions and work with large datasets to support key business initiatives.

The role requires expert Snowflake experience, strong data warehousing knowledge and proficiency in Python, dbt, Airflow or Azure Data Factory, with AWS/Azure cloud exposure preferred.

Qualifications

• 5+ years experience as a Data Engineer.
• Expert-level Snowflake experience.
• Strong understanding of data warehousing and data modelling.
• Experience building ETL/ELT pipelines.
• Experience with Python and/or modern data engineering tools such as dbt, Airflow or Azure Data Factory.
• Cloud experience across AWS or Azure is highly desirable
• Finance/Banking experience is preferable

Responsibilities

• Design, build and maintain ETL/ELT data pipelines.
• Develop and optimise complex SQL queries within Snowflake.
• Build and maintain Snowflake data models and architecture.
• Integrate data from multiple sources across cloud and on-premise environments.
• Optimise data pipelines and Snowflake workloads for performance and scalability.
• Ensure data quality, reliability and security across the platform.

Skills

Snowflake expert

ETL/ELT pipelines

Data warehousing

Data modelling

Python

dbt

Airflow

Azure/AWS cloud

5+ years experience

Finance/Banking experience

Tools

dbt

Airflow

Azure Data Factory

Python

Job description

Charterhouse is seeking an experienced Data Engineer with strong Snowflake expertise to join a growing data and technology team on a contract basis. You will design, build and maintain ETL/ELT pipelines, develop Snowflake data solutions and work with large datasets to support key business initiatives.

The role requires expert Snowflake experience, strong data warehousing knowledge and proficiency in Python, dbt, Airflow or Azure Data Factory, with AWS/Azure cloud exposure preferred.