Data Testing Lead - Snowflake, Airflow & Automation

Hydrogen Group; Sydney; On-site; AUD 90,000 - 140,000; Full time

Job summary

Hydrogen Group is seeking an experienced Data Tester to join a leading financial services organisation in Sydney. You will design and execute testing strategies across complex data pipelines, with a strong focus on automated data validation and pipeline quality.

You will work closely with data engineers, developers and business stakeholders to ensure data accuracy, completeness and reliability across modern cloud data platforms.

Qualifications

• 8+ years' experience in data testing, ETL testing, data quality or data engineering QA.
• Strong hands-on experience with Snowflake.
• Advanced SQL skills and experience querying and validating large datasets.

Responsibilities

• Develop and execute data testing and QA strategies for enterprise data platforms.
• Perform ETL/ELT, data warehouse, data pipeline and integration testing.
• Write complex SQL to validate data transformations and data quality.
• Test data in Snowflake: tables, views, stored procedures, transformation logic.
• Validate data ingestion and transformation across source/target systems.
• Work with Airflow to test pipeline workflows, DAGs and scheduling.
• Develop automated tests integrated into Airflow pipelines and CI/CD processes.
• Implement automated data quality checks for completeness, accuracy, uniqueness, referential integrity.
• Validate pipeline execution and downstream impacts.
• Investigate data issues by tracing failures through Airflow, sources, and Snowflake.

Skills

Snowflake

SQL

Airflow

Test automation

ETL testing

Tools

Python

Job description

Hydrogen Group is seeking an experienced Data Tester to join a leading financial services organisation in Sydney. You will design and execute testing strategies across complex data pipelines, with a strong focus on automated data validation and pipeline quality.

You will work closely with data engineers, developers and business stakeholders to ensure data accuracy, completeness and reliability across modern cloud data platforms.