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QA Data Specialist at Enroute. About Enroute:. We love technology, and we enjoy what we do. We are always looking for innovation. We have social awareness and try to improve it daily. We make things happen. You can trust us. Our Enrouters are always up for a challenge. We ask questions, and we love to learn.. We pride ourselves on having great benefits and compensations, a fantastic work environment, flexible schedules, and policies that positively impact the balance of work and life outside of it. We care about who you are in the office and as an individual. We get involved, we like to know our people, we want every Enrouter to become part of a great community of highly driven, responsible, respectful, and above all, happy people. We want you to enjoy working with us.. We’re looking for a . QA Data Engineer. to join our growing team and ensure the integrity and quality of large-scale data operations. This is a cross-functional role blending . Quality Assurance. , . Data Engineering. , and . analytical problem-solving. . If you’re passionate about clean, reliable data and enjoy working with large datasets, cloud platforms, and QA best practices — we want to hear from you.. . 3+ years of experience in Quality Assurance . . 3+ years of experience in Data Engineering . . 1+ years with object-oriented programming (preferably Python) . . 1+ years of experience with Git . . Strong understanding of data quality principles and best practices . . Strong SQL skills and knowledge of data warehousing concepts . . Experience analyzing large datasets and identifying inconsistencies . . Understanding of API testing and data consumption . . Familiarity with cloud platforms (AWS, GCP, or Azure) . . Experience with data quality tools and technologies . . Basic experience with data visualization tools (e.g., Tableau, Looker, Power BI) . . Strong analytical, communication, and interpersonal skills. . . Key Responsibilities. . Validate and verify the accuracy and consistency of data across systems . . Implement QA best practices for data pipelines and analytics workflows . . Conduct root cause analysis on data anomalies and report findings . . Maintain documentation and reporting for quality assurance efforts . . Collaborate with engineering teams to test and improve ETL processes . . Communicate data issues and quality metrics to stakeholders . . Support QA Ops through testing automation and process optimization . . Perform API testing and ensure integration points meet data standards. . Company Location: Mexico.