Senior QA Engineer – Data & Analytics

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior QA Engineer – Data & Analytics based in Brazil.

This is a hands-on senior QA role focused on ensuring the accuracy, reliability, and integrity of data products across complex, large-scale <environments.You> will work across data pipelines, lakes, warehouses, migrations, analytics platforms, and downstream reporting.The role partners closely with Data Engineers, Analysts, Developers, and other stakeholders to embed quality throughout the data <lifecycle.You> will define validation strategies, investigate discrepancies, and help establish strong data quality and observability practices.SQL will be central to reconciliation, troubleshooting, and end-to-end validation of data transformations and <integrations.You> will also contribute to automation, performance testing, governance, security, and cloud data platform initiatives.This is an opportunity to influence how business-critical data is trusted, monitored, and delivered within an Agile international environment.

Accountabilities

• Define and implement data quality and validation strategies across data pipelines, data lakes, warehouses, and analytics platforms.
• Test data throughout its lifecycle, validating accuracy, completeness, consistency, integrity, freshness, and reliability.
• Validate ETL/ELT pipelines, transformations, integrations, and data flows from source systems through downstream analytics.
• Develop and execute end-to-end data validation, reconciliation, exploratory testing, and discrepancy-investigation activities using SQL extensively.
• Collaborate with engineering teams on data contracts, schema validation, anomaly detection, and automated quality controls.
• Support data quality automation through frameworks such as Great Expectations or equivalent solutions.
• Validate BI and analytics outputs to ensure reports and insights accurately represent the underlying data.
• Support large-scale data migration testing, helping protect data integrity and business continuity during cloud or platform transitions.
• Define and monitor validation criteria, data freshness SLAs, quality metrics, and other indicators of data reliability.
• Contribute to data observability, lineage, governance, monitoring, security, privacy, and compliance initiatives.
• Investigate recurring data quality issues, identify root causes, and partner with engineering teams to implement preventative improvements.
• Support performance and scalability testing across data platforms, including query performance, reliability, and large-volume processing.
• Work within an Agile, cross-functional environment while advocating for quality and challenging assumptions when necessary.

Requirements

• Strong professional experience in QA for data-focused projects, rather than primarily application or UI testing.
• Hands-on experience testing data pipelines, ETL/ELT processes, data transformations, and integrations.
• Strong SQL skills with practical experience in data validation, reconciliation, troubleshooting, and root-cause analysis.
• Solid understanding of data engineering workflows and data lake/data warehouse architectures.
• Experience testing APIs, integrations, and data flows in cloud environments such as GCP, AWS, or Azure.
• Experience with data quality frameworks such as Great Expectations or similar tools.
• Experience validating data across multiple systems and environments and investigating inconsistencies between them.
• Understanding of BI and analytics validation, ideally involving platforms such as ThoughtSpot, Power BI, Looker, or Tableau.
• Strong analytical, problem-solving, investigative, and attention-to-detail skills.
• Excellent communication and collaboration skills, with the ability to work effectively with Data Engineers, Analysts, Developers, and business stakeholders.
• A proactive quality mindset and the confidence to promote data quality throughout the development lifecycle.
• Experience working in Agile and cross-functional teams.
• Strong written and spoken English communication skills.
• Experience with large-scale cloud or data-platform migrations, particularly Databricks-to-GCP environments, is highly desirable.
• Experience with Databricks and/or GCP, data observability, lineage tracking, monitoring, performance testing, governance, security, or privacy is a plus.
• Exposure to machine-learning model validation or AI testing is advantageous.

Benefits

• Remote work from Brazil or other approved locations.
• Collegial and collaborative international working environment.
• Shared responsibility and autonomy, with opportunities to contribute to the team culture.
• Agile environment where ideas, initiative, and continuous improvement are encouraged.
• Opportunities to work on different projects and expand your technical experience.
• Ongoing training and mentoring.
• Opportunities for professional growth and development.
• Potential opportunities to travel.