Senior Data Tester

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

We are looking for an experienced Data Tester with strong Snowflake, SQL, Apache Airflow and test automation experience to join our data and technology team within a leading financial services organisation.

You'll play a key role in ensuring the accuracy, completeness, integrity and reliability of critical data across modern cloud data platforms and data pipelines.

Working closely with data engineers, developers, analysts and business stakeholders, you'll design and execute testing strategies across complex data pipelines, with a strong focus on automated data validation and pipeline quality.

What You'll Do

• Develop and execute comprehensive data testing and quality assurance strategies across enterprise data platforms.
• Perform ETL/ELT, data warehouse, data pipeline and integration testing.
• Write complex SQL to validate data transformations, reconciliations, business rules and data quality.
• Test data within Snowflake, including tables, views, stored procedures and transformation logic.
• Validate data ingestion and transformation across source and target systems.
• Work with Apache Airflow to understand, test and validate data pipeline workflows, DAGs, dependencies and scheduling.
• Develop automated tests and validation checks that can be integrated into Airflow pipelines and CI/CD processes.
• Implement automated data quality checks covering areas such as completeness, accuracy, uniqueness, referential integrity and reconciliation.
• Validate pipeline execution, including successful/failed DAG runs, dependencies, retries, error handling and downstream impacts.
• Investigate data issues by tracing failures through Airflow workflows, source systems and Snowflake transformations.
• Identify opportunities to replace manual testing with repeatable and automated test processes.
• Contribute to the development and maintenance of automated regression test suites for data pipelines.
• Integrate automated testing into the broader CI/CD and DevOps lifecycle.
• Identify, investigate and document defects, working closely with engineering teams through to resolution.
• Support regression, system integration and end-to-end testing.
• Review technical and business requirements and translate them into effective test scenarios and automated validation rules.

About You

You'll be a hands-on data testing professional who understands both data quality and modern data engineering practices. You'll be comfortable working with large datasets, investigating complex pipeline issues and building automation that improves confidence in data releases.

You’ll ideally have:

• 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.
• Practical experience with Apache Airflow, including DAGs, task dependencies, scheduling, monitoring and troubleshooting.
• Experience designing and implementing automated data tests and data quality checks.
• Strong understanding of data warehouses, data modelling and ETL/ELT processes.
• Experience testing complex data pipelines and integrations across multiple systems.
• Experience with Python or another programming language used for test automation.
• Understanding of CI/CD pipelines and how automated tests can be incorporated into the software/data delivery lifecycle.
• Excellent communication skills, with the ability to work effectively with technical and business stakeholders.
• Experience within banking, financial services, insurance or another regulated environment is highly desirable.

Nice to Have

• Experience integrating automated tests with Airflow.
• Exposure to AWS, Azure or GCP.
• Experience with Git, CI/CD and DevOps practices.
• Understanding of financial data, regulatory reporting or risk data.
• Familiarity with Agile/Scrum delivery environments.

About the Role

We are looking for an experienced Data Tester with strong Snowflake, SQL, Apache Airflow and test automation experience to join our data and technology team within a leading financial services organisation.

You'll play a key role in ensuring the accuracy, completeness, integrity and reliability of critical data across modern cloud data platforms and data pipelines.

Working closely with data engineers, developers, analysts and business stakeholders, you'll design and execute testing strategies across complex data pipelines, with a strong focus on automated data validation and pipeline quality.

What You'll Do

• Develop and execute comprehensive data testing and quality assurance strategies across enterprise data platforms.
• Perform ETL/ELT, data warehouse, data pipeline and integration testing.
• Write complex SQL to validate data transformations, reconciliations, business rules and data quality.
• Test data within Snowflake, including tables, views, stored procedures and transformation logic.
• Validate data ingestion and transformation across source and target systems.
• Work with Apache Airflow to understand, test and validate data pipeline workflows, DAGs, dependencies, scheduling.
• Develop automated tests and validation checks that can be integrated into Airflow pipelines and CI/CD processes.
• Implement automated data quality checks covering areas such as completeness, accuracy, uniqueness, referential integrity and reconciliation.
• Validate pipeline execution, including successful/failed DAG runs, dependencies, retries, error handling and downstream impacts.
• Investigate data issues by tracing failures through Airflow workflows, source systems and Snowflake transformations.
• Identify opportunities to replace manual testing with repeatable and automated test processes.
• Contribute to the development and maintenance of automated regression test suites for data pipelines.
• Integrate automated testing into the broader CI/CD and DevOps lifecycle.
• Identify, investigate and document defects, working closely with engineering teams through to resolution.
• Support regression, system integration and end-to-end testing.
• Review technical and business requirements and translate them into effective test scenarios and automated validation rules.

About You

You'll be a hands-on data testing professional who understands both data quality and modern data engineering practices. You'll be comfortable working with large datasets, investigating complex pipeline issues and building automation that improves confidence in data releases.

You’ll ideally have:

• 8+ years' experience in data testing, ETL testing, data quality or data engineering QA.
• Strong hands-on experience with Snowflake.
• Strong Python automation experience.
• Advanced SQL skills and experience querying and validating large datasets.
• Practical experience with Apache Airflow, including DAGs, task dependencies, scheduling, monitoring and troubleshooting.
• Experience designing and implementing automated data tests and data quality checks.
• Strong understanding of data warehouses, data modelling and ETL/ELT processes.
• Experience testing complex data pipelines and integrations across multiple systems.
• Experience with Python or another programming language used for test automation.
• Understanding of CI/CD pipelines and how automated tests can be incorporated into the software/data delivery lifecycle.
• Excellent communication skills, with the ability to work effectively with technical and business stakeholders.
• Experience within banking, financial services, insurance or another regulated environment is highly desirable.

Nice to Have

• Experience integrating automated tests with Airflow.
• Exposure to AWS, Azure or GCP.
• Experience with Git, CI/CD and DevOps practices.
• Understanding of financial data, regulatory reporting or risk data.
• Familiarity with Agile/Scrum delivery environments.

Desired Skills and Experience

About the Role

We are looking for an experienced Data Tester with strong Snowflake, SQL, Apache Airflow and test automation experience to join our data and technology team within a leading financial services organisation.

You'll play a key role in ensuring the accuracy, completeness, integrity and reliability of critical data across modern cloud data platforms and data pipelines.

Working closely with data engineers, developers, analysts and business stakeholders, you'll design and execute testing strategies across complex data pipelines, with a strong focus on automated data validation and pipeline quality.

What You’ll Do

• Develop and execute comprehensive data testing and quality assurance strategies across enterprise data platforms.
• Perform ETL/ELT, data warehouse, data pipeline and integration testing.
• Write complex SQL to validate data transformations, reconciliations, business rules and data quality.
• Test data within Snowflake, including tables, views, stored procedures and transformation logic.
• Validate data ingestion and transformation across source and target systems.
• Work with Apache Airflow to understand, test and validate data pipeline workflows, DAGs, dependencies and scheduling.
• Develop automated tests and validation checks that can be integrated into Airflow pipelines and CI/CD processes.
• Implement automated data quality checks covering areas such as completeness, accuracy, uniqueness, referential integrity and reconciliation.
• Validate pipeline execution, including successful/failed DAG runs, dependencies, retries, error handling and downstream impacts.
• Investigate data issues by tracing failures through Airflow workflows, source systems and Snowflake transformations.
• Identify opportunities to replace manual testing with repeatable and automated test processes.
• Contribute to the development and maintenance of automated regression test suites for data pipelines.
• Integrate automated testing into the broader CI/CD and DevOps lifecycle.
• Identify, investigate and document defects, working closely with engineering teams through to resolution.
• Support regression, system integration and end-to-end testing.
• Review technical and business requirements and translate them into effective test scenarios and automated validation rules.

About You

You'll be a hands-on data testing professional who understands both data quality and modern data engineering practices. You'll be comfortable working with large datasets, investigating complex pipeline issues and building automation that improves confidence in data releases.

You’ll ideally have:

• 8+ years' experience in data testing, ETL testing, data quality or data engineering QA.
• Strong hands-on experience with Snowflake.
• Strong Python automation experience.
• Advanced SQL skills and experience querying and validating large datasets.
• Practical experience with Apache Airflow, including DAGs, task dependencies, scheduling, monitoring and troubleshooting.
• Experience designing and implementing automated data tests and data quality checks.
• Strong understanding of data warehouses, data modelling and ETL/ELT processes.
• Experience testing complex data pipelines and integrations across multiple systems.
• Experience with Python or another programming language used for test automation.
• Understanding of CI/CD pipelines and how automated tests can be incorporated into the software/data delivery lifecycle.
• Excellent communication skills, with the ability to work effectively with technical and business stakeholders.
• Experience within banking, financial services, insurance or another regulated environment is highly desirable.

Nice to Have

• Experience integrating automated tests with Airflow.
• Exposure to AWS, Azure or GCP.
• Experience with Git, CI/CD and DevOps practices.
• Understanding of financial data, regulatory reporting or risk data.
• Familiarity with Agile/Scrum delivery environments.