Job Description

5–8 years of experience in data quality, QA engineering, or data testing, with direct exposure to wealth management data domains
Hands-on experience validating wealth management datasets including positions, transactions, accounts, clients, advisors, and security master data
Experience designing and executing reconciliation QA processes across custodians, platforms, or internal financial systems
Proficiency with SQL and at least one scripting language (Python preferred) for building automated data validation and testing workflows
Experience working within Microsoft Azure cloud environments (Azure Data Factory, Azure Data Lake, or equivalent)
Strong understanding of ETL/ELT pipeline architecture and the ability to test at each layer of a data pipeline
Demonstrated use of AI tools in day-to-day QA work — we expect QA leads to be actively leveraging AI to improve coverage and efficiency
Strong documentation skills — test plans, data quality runbooks, and root cause analyses should be second nature

QA Lead - Data Quality

Quick Overview