Job description for ETL Testing & Automation at PT Leap Digital Indonesia
Role Overview
We are seeking experienced ETL Testing & Automation Engineers to support data validation and quality assurance for large-scale data platforms. This role involves ensuring the accuracy, completeness, and reliability of data across end-to-end ETL pipelines, including migrations and system integrations.
Key Responsibilities
- Perform end-to-end testing of ETL processes (data ingestion, transformation, and loading)
- Validate source-to-target mappings, business rules, and data consistency
- Conduct data migration testing (completeness, accuracy, reconciliation)
- Execute complex SQL queries for data validation across multiple layers (source, staging, target)
- Validate ETL workflows, job scheduling, and error handling processes
- Develop and execute automation scripts for ETL regression and validation testing
- Support API and integration data validation where applicable
- Collaborate with data engineers, developers, and business stakeholders to resolve data issues
- Prepare test cases, execution reports, and defect documentation
- Ensure compliance with data quality standards and QA governance
Requirements
Mandatory Skills & Experience
- 5–10 years of experience in ETL / Data Testing
- Strong SQL skills (joins, aggregations, reconciliation queries)
- Hands-on experience with ETL tools (e.g., Informatica, Talend, DataStage, or similar)
- Experience in Data Warehouse or Data Lake testing
- Solid understanding of data validation and reconciliation techniques
- Experience in ETL test automation (Python, shell scripting, or similar)
Preferred Qualifications
- Experience with cloud data platforms (e.g., GCP, BigQuery)
- Exposure to API testing and integration validation
- Experience in large-scale or enterprise data environments
- Familiarity with Agile delivery methodologies
- Experience with defect tracking tools (e.g., JIRA)
- Additional Information
- Opportunity to work on high-impact, large-scale data transformation programs
- Collaborative environment with cross-functional teams
- Fast-paced project with strong emphasis on data quality and reliability
