Data Quality Assurance Engineer (Temporary)

About You

You are a Data Quality Assurance Engineer who enjoys ensuring the accuracy, completeness, and reliability of data across complex data environments. You have hands-on experience validating high-volume datasets, testing ETL processes, and using SQL to identify data inconsistencies and verify expected results.

You are analytical, detail-oriented, and comfortable working across databases, Big Data environments, and backend systems. You bring a strong quality mindset to data-driven solutions and enjoy collaborating with technical teams to identify defects, validate data integrity, and continuously improve testing practices.

Note: This role operates under a 3-month contractor model.

Responsibilities

Perform data quality validations to ensure the accuracy, completeness, and integrity of data processing within Google Cloud Platform (GCP) environments.; Write medium to complex SQL queries to perform data validation and verify expected results.; Test and validate ETL processes and data transformations throughout the data lifecycle.; Perform testing and verification of backend applications, databases, Big Data environments, and related tools following established best practices.; Verify the capture of analytics events in related file systems or databases using SQL or scripting languages such as Python or Shell.; Develop, maintain, and execute regression automation for GUI applications, backend services, and ETL processes.; Identify, document, track, and communicate defects discovered during testing.; Create and maintain test plans, test cases, and supporting QA documentation.; Collaborate with technical teams to investigate data-quality issues and support defect resolution.

Requirements

Bachelor’s Degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field is desired, or equivalent professional experience.; 1+ years of professional experience in Big Data and Data Quality Testing.; Experience applying data profiling techniques when working with high volumes of data.; Hands-on experience testing ETL processes and validating data throughout the data lifecycle.; Strong experience with SQL for data validation and testing purposes, including writing medium to complex queries.; Solid understanding of relational and non-relational databases, including data integrity verification.; Experience working with scheduling and orchestration tools such as Airflow, AutoSys, or similar technologies.; Experience working with test management tools such as ALM and requirement/defect management tools such as Jira.; Experience creating, documenting, maintaining, and executing test plans and test cases.; Experience documenting, tracking, and communicating defects throughout the testing lifecycle.; Strong analytical and problem-solving skills with a solid quality assurance mindset.; Excellent written and verbal communication skills.; Full Professional English proficiency.; Hands-on experience with ETL testing, data profiling, and high-volume data validation.; Strong SQL skills for data validation and testing.; Experience with relational and non-relational databases.; Experience with scheduling/orchestration tools such as Airflow or AutoSys.; Experience creating and executing test plans and test cases.