LatAm - Sr. QA Data Migration Engineer

hace 1 semana


Argentina Perficient A tiempo completo

Senior QA Data Migration Engineer to join our high-performing team located in LatAm. As a Senior Technical Consultant, you will drive the quality assurance strategy for complex data migration projects, moving legacy on‑premise data to modern AWS cloud architectures. You will participate in all aspects of the data lifecycle, including estimation, test strategy design, automated script implementation, data validation, and documentation. As a member working in a collaborative agile environment, you will take direction from Data Architects and Leads to ensure zero data loss and high fidelity for our clients. Perficient is always looking for the best and brightest talent and we need you We are a quickly growing, global digital consulting leader transforming the world’s largest enterprises. You will work with the latest cloud technologies, expand your Data Engineering skills, and become a part of our global community of diverse and knowledgeable colleagues. Responsibilities Data Validation Strategy: Design, code, and execute automated test scripts to validate data integrity, completeness, and accuracy between source (Legacy/On‑Prem) and target (AWS Cloud) systems. Pipeline Testing: Analyze and test ETL/ELT pipelines using AWS Glue, Lambda, or Step Functions to ensure data transformation logic meets business requirements. Automation Development: Develop robust automated testing frameworks using Python and SQL to perform row counts, column mapping, and checksum validations on large datasets. AWS Integration: Validate data ingestion and storage flows involving AWS services such as S3, Redshift, RDS, and DynamoDB . Migration Tools: utilize AWS Database Migration Service (DMS) and Schema Conversion Tool (SCT) to monitor replication tasks and identify discrepancies. Defect Management: Lead root cause analysis for data discrepancies, parsing log files (CloudWatch), and working closely with Data Engineers to resolve ETL defects. CI/CD & AI: Integrate data testing scripts into CI/CD pipelines (GitLab/Azure DevOps). Utilize AI tools (Github Copilot, Anthropic Claude) to optimize SQL queries and generate test data scenarios. Collaboration: Ensure technical data governance processes are followed and effectively communicate data quality metrics to non‑technical stakeholders. Qualifications Technical Background: Passionate data advocate with 3-5+ years of experience in Data Quality, Data Engineering, or Backend QA. Core Languages: Strong proficiency in SQL (complex joins, stored procedures) and Python (Pandas, Boto3, PyTest) for scripting automated validations. AWS Expertise: Breadth of experience with AWS Data ecosystems, specifically S3, Glue, Redshift, Athena, and DMS (Database Migration Service). Testing Frameworks: Experience with data testing tools such as Great Expectations , dbt tests, or custom Python frameworks. Analytical Skills: Strong debugging and investigative skills. Ability to assimilate disparate information from database logs and error messages to find the root cause of data skew or corruption. Methodology: Experience with Agile/Scrum methodology and working with high‑volume datasets. Education: Bachelor’s Degree in Computer Science, Math, Engineering, Data Science, or comparable major. Communication: Strong consulting skills with the ability to explain complex data issues to various organizations. Benefits Perficient full‑time employees receive complete and competitive benefits, including paid time off plus holidays and a generous work/life program. Job Information Job Identification Job Category Platforms & Technology Posting Date 11/19/2025, 01:49 PM Job Schedule Full time Disclaimer: The above statements are not intended to be a complete statement of job content, rather to act as a guide to the essential functions performed by the employee assigned to this classification. Management retains the discretion to add or change the duties of the position at any time. Perficient, Inc. proudly provides equal employment opportunity (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, or status as a protected veteran in accordance with applicable federal, state and local laws. #J-18808-Ljbffr



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