Data Quality Engineering Services
Seeking to hire a long-term Contractor based out of Argentina, Brazil, Colombia, Costa Rica, or Mexico for a Data Quality Engineer with strong technical expertise and hands-on experience in ensuring the quality and accuracy of data. You will play a key role in developing and implementing data Quality standards and procedures, ensuring the integrity of reports, dashboards, and data exports.
Scope of Services:
Develop, maintain, and execute various data testing approaches, including validating data sources, applying/validating transform logic, and ensuring data accuracy.
Design, execute, and maintain regression tests that cover data quality, transformation logic, aggregation rules, and business logic validation.
Contribute to ensuring data testing best practices are included in CI and deployment steps.
Identify root causes for data quality defects and develop sustainable countermeasures.
Monitor reporting & BI (Tableau) dashboards and proactively identify anomalies, inconsistencies, and gaps.
Develop and maintain automated test scripts for data validation using Python-based frameworks or similar.
Write SQL queries to validate data integrity and ensure analytical outputs are aligned with business requirements within the data testing frameworks.
Partner with data engineers and business intelligence developers to verify model accuracy, statistical outputs, and integration of analytical components.
Support validation of AI/ML models by testing input/output integrity and ensuring model-driven results are aligned with business logic.
Skills & Experience:
Proficiency in SQL writing complex queries, joins, and aggregations used in validating analytical outputs.
Hands-on testing experience with data quality/integrity testing frameworks such as Great Expectations.
Python experience for scripting, data validation, and automation.
Exposure to BI/analytics tools such as Tableau, Power BI, or similar
2 or more years of experience in Quality engineering with a strong focus on data testing, analytics validation, and Business Intelligence/Extract, Transform, Load (BI/ETL) systems.
Knowledge of Agile methodologies such as Scrum and Kanban
Strong communication abilities with data engineers and data stakeholders relating to data system changes and data inquiries
Ability to develop a deep domain knowledge of relevant business data models
Preferred Technical but not Required
Experience with DBT best practices.
Experience with Semantic Layer tools (ie Metric Flow, Cube, DataPlex or similar)
Please note that given the nature of the contract, this role will not be eligible to participate in company-sponsored benefits.
#LI-Remote
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Data Quality Engineering Services
Seeking to hire a long-term Contractor based out of Argentina, Brazil, Colombia, Costa Rica, or Mexico for a Data Quality Engineer with strong technical expertise and hands-on experience in ensuring the quality and accuracy of data. You will play a key role in developing and implementing data Quality standards and procedures, ensuring the integrity of reports, dashboards, and data exports.
Scope of Services:
Develop, maintain, and execute various data testing approaches, including validating data sources, applying/validating transform logic, and ensuring data accuracy.
Design, execute, and maintain regression tests that cover data quality, transformation logic, aggregation rules, and business logic validation.
Contribute to ensuring data testing best practices are included in CI and deployment steps.
Identify root causes for data quality defects and develop sustainable countermeasures.
Monitor reporting & BI (Tableau) dashboards and proactively identify anomalies, inconsistencies, and gaps.
Develop and maintain automated test scripts for data validation using Python-based frameworks or similar.
Write SQL queries to validate data integrity and ensure analytical outputs are aligned with business requirements within the data testing frameworks.
Partner with data engineers and business intelligence developers to verify model accuracy, statistical outputs, and integration of analytical components.
Support validation of AI/ML models by testing input/output integrity and ensuring model-driven results are aligned with business logic.
Skills & Experience:
Proficiency in SQL writing complex queries, joins, and aggregations used in validating analytical outputs.
Hands-on testing experience with data quality/integrity testing frameworks such as Great Expectations.
Python experience for scripting, data validation, and automation.
Exposure to BI/analytics tools such as Tableau, Power BI, or similar
2 or more years of experience in Quality engineering with a strong focus on data testing, analytics validation, and Business Intelligence/Extract, Transform, Load (BI/ETL) systems.
Knowledge of Agile methodologies such as Scrum and Kanban
Strong communication abilities with data engineers and data stakeholders relating to data system changes and data inquiries
Ability to develop a deep domain knowledge of relevant business data models
Preferred Technical but not Required
Experience with DBT best practices.
Experience with Semantic Layer tools (ie Metric Flow, Cube, DataPlex or similar)
Please note that given the nature of the contract, this role will not be eligible to participate in company-sponsored benefits.
#LI-Remote