Data Quality Assurance Analyst

01 Августа

Партнерские Вакансии

Компания "ОнТаргет ЛАБС"

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