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| AWS Lakehouse Data Quality Assurance Testing Lead (10+ Years Experience) We are seeking an experienced AWS Lakehouse Data Quality Assurance Testing Lead with 10+ years of experience in data warehousing, data engineering, and quality assurance testing across cloud-based data platforms. The ideal candidate will lead end-to-end data validation and quality assurance initiatives for modern AWS Lakehouse architectures leveraging AWS S3, Apache Iceberg Tables, AWS Glue, DBT, Snowflake, and Amazon Athena. The role requires strong expertise in designing and executing data quality frameworks, validating large-scale ETL/ELT pipelines, developing automated test strategies, and ensuring data integrity, completeness, accuracy, consistency, and lineage across bronze, silver, and gold data layers. The candidate should have hands-on experience with SQL, Python, data reconciliation, metadata validation, schema evolution testing, Iceberg table validations, and performance testing of analytical workloads. Responsibilities include defining QA standards, building automated testing solutions, collaborating with data engineers, architects, and business stakeholders, leading defect triage, ensuring compliance with data governance standards, and driving continuous improvements in data quality processes. Experience with Agile delivery methodologies, CI/CD integration, cloud-native testing tools, and large-scale enterprise data lake modernization programs is highly desirable. Strong leadership, stakeholder management, and communication skills are essential to lead distributed teams and ensure successful delivery of high-quality data products in a modern AWS Lakehouse ecosystem. Relevant technologies include AWS S3, Apache Iceberg, AWS Glue, DBT, Snowflake, Amazon Athena, Python, SQL, Spark, Airflow, Data Quality Frameworks, Data Governance, and Test Automation. |
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