ETL Test Automation Engineer

Salary: ₱90,000 – ₱120,000 per month

Job Description

• Design, develop, and maintain automated testing frameworks for ETL/ELT processes and data pipelines.

• Develop and execute automated regression tests to ensure data accuracy, consistency, and quality.

• Perform data validation, source-to-target reconciliation, schema validation, and data quality checks.

• Implement automated data quality checks for accuracy, latency, performance, and security.

• Integrate automated testing into CI/CD pipelines using Azure DevOps or similar tools.

• Develop reusable test scripts and automation solutions using Python and SQL.

• Support testing of data warehouse and data integration platforms, including SQL Server, SSIS, dbt, Fivetran, and Databricks.

• Identify, troubleshoot, and resolve data quality issues in collaboration with Data Engineers and QA teams.

• Prepare test reports, monitor automation coverage, and maintain testing documentation.

• Collaborate with technical teams to improve testing processes and automation standards.

Job Qualifications

• Bachelor's degree in Computer Science, Information Technology, Computer Engineering, or a related field.

• At least 4 years of experience in Test Automation or Data Engineering, with hands-on experience in ETL/ELT or data pipeline testing.

• Strong programming skills in Python and SQL, particularly in developing automated test scripts and reusable testing frameworks.

• Experience in ETL/ELT testing, data validation, data reconciliation, and automated regression testing.

• Hands-on experience with testing frameworks such as pytest, Great Expectations, dbt tests, Soda, or similar tools.

• Experience integrating automated tests into CI/CD pipelines using Azure DevOps or equivalent tools.

• Good understanding of data warehousing, data integration, and ETL/ELT processes.

• Ability to work independently, troubleshoot technical issues, and collaborate with cross-functional teams.

• Good verbal and written communication skills.

Preferred Qualifications

• Experience with Databricks, PySpark, Delta Lake, or other Big Data platforms.

• Knowledge of data quality monitoring, anomaly detection, and data pipeline performance testing.

• Experience with SQL Server, SSIS, dbt, or Fivetran.

• Familiarity with AI-assisted development or testing tools such as GitHub Copilot or Claude.

• Databricks certification is an advantage.

• Experience in the Banking or Financial Services industry is a plus.