Full Description

Job Summary We are looking for a detail-oriented Data Quality Engineer / Data QA to ensure the accuracy, completeness, and reliability of our modern AWS-based data platform. You will act as the gatekeeper of data trust, bringing a deep understanding of financial data domains (spending, lending, deposits) to define comprehensive data quality rules from every angle. You will work closely with Data Architects, Data Engineers, Business Analysts, Data Governance, source-system teams, and business users to define data-quality requirements, rules, processes, and operational workflows. A strong understanding of data and business context is important, as the candidate will be responsible for defining and maintaining data-quality rules that cover different dimensions such as completeness, accuracy, consistency, uniqueness, validity, integrity, and timeliness.

Key Responsibilities Define and execute data-quality and data-validation checks across source systems, data pipelines, and target datasets. Validate data completeness, accuracy, consistency, uniqueness, timeliness, and business-rule compliance. Perform source-to-target reconciliation, record-count validation, duplicate checks, null checks, and transformation-rule validation. Design and execute test scenarios for ETL/ELT pipelines across SIT, UAT, production deployment, and data backfill activities. Investigate data discrepancies, work with Data Engineers and source-system teams to identify root causes, and track issues through resolution. Develop reusable SQL-based or automated data-quality checks to improve testing efficiency and reduce manual validation. Support production monitoring, incident investigation, data-quality reporting, and continuous improvement of data-quality controls. Qualifications At least 2–4 years of experience in Data Quality, Data QA, ETL Testing, Data Testing, Business Intelligence Testing, or a related role. Strong SQL skills for querying, validation, reconciliation, aggregation, and data analysis. Experience with data-quality checks such as completeness, accuracy, uniqueness, consistency, validity, and timeliness. Experience preparing test scenarios, test cases, expected results, and defect reports for data-related projects. Ability to investigate data discrepancies and identify potential root causes. Good communication and collaboration skills when working with Data Engineers, Business Analysts, source-system teams, and business users. Nice-to-Have Experience working in banking, financial services, or another regulated industry. Familiarity with AWS data services (e.g., S3, Athena, Glue, Redshift) and querying data directly from cloud storage. Practical understanding of databases, data warehouses, data lakehouse, ETL/ELT pipelines, and data models. Experience with data-quality frameworks, automated testing tools, or data-observability platforms. Basic understanding of data governance, metadata, data lineage, data classification, and sensitive-data handling.

Benefits

• Hybrid Working Arrangement
• World-Class Development Program
• Performance Bonus
• Vacation Leave 15 Days + Maternity Leave
• MacBook Provided
• Housing Loan
• Life Insurance/ Health Insurance/ Dental Care
• Jetts Fitness (Corporate rate and privilege)
• Opportunity to be a part of team that drives Thailand Digital Economy (The contributor of the great impact to millions of Thai people through digital platforms e.g. PaoTang App. and Krungthai Next App)

Working Location

• The ParQ ชั้น 5, 9-10
• ติดกับ MRT สถานีศูนย์การประชุมแห่งชาติสิริกิติ์ ทางออกที่ 2