Заместитель директора по регионам
ЗП не указана
Опыт работы:от 1 до 3 лет, полный день, полная занятость
About the Role
We are looking for a detail-oriented Data QA Analyst to join our Data & AI practice supporting financial services clients. In this role, you will validate data accuracy and integrity across automated data pipelines and reporting outputs, ensuring that financial data meets quality standards before it reaches business stakeholders.
This is a hands-on individual contributor role focused on systematic data validation. You will work from defined test cases, source data specifications, and report outputs provided to you — no BI development or dashboard building is required.
Key Responsibilities
Execute structured data quality test plans across financial data pipelines and reporting layers
Validate report outputs against source data, business rules, and expected financial calculations
Identify, document, and track data discrepancies, anomalies, and reconciliation gaps
Work closely with data engineers and business analysts to triage and prioritize defects
Contribute to the development and maintenance of automated data validation scripts and frameworks
Maintain clear, audit-ready documentation of test results and QA findings
Support UAT and regression testing cycles for data platform enhancements
Required Qualifications
2+ years of experience in data quality assurance, data testing, or a closely related role
Solid understanding of financial processes — familiarity with concepts such as GL entries, reconciliations, period-end reporting, or financial statement structures
Proficiency in SQL for querying and comparing datasets
Experience reading and interpreting tabular reports and financial data outputs (Excel, CSV, or report extracts)
Methodical, structured approach to testing with strong attention to detail
Clear written communication skills for defect reporting and test documentation
Nice to Have
Exposure to data pipeline or ETL testing (Databricks, dbt, or similar)
Familiarity with test automation tools or scripting (Python, pytest, Great Expectations)
Experience in a consulting or professional services environment
Knowledge of data governance or data quality frameworks
What We Offer
Exposure to large-scale financial data environments across multiple clients and verticals
A collaborative, technical team with strong data engineering and AI capabilities
Clear growth path toward senior QA, data engineering, or data governance roles
Flexible working arrangements
Объявление ID,
3 просмотра (+1 за сегодня),
Дата размещения 19.07.2026г.,
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