> Markdown version of [/jobs/ext/3647350-data-quality-engineer](https://www.wearedevelopers.com/jobs/ext/3647350-data-quality-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Quality Engineer - **Company:** HCL America Inc. - **Location:** Medina, WA, United States - **Salary:** $78,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Amazon Web Services, Amazon S3, Data Transformation, Python (Programming Language), DataOps, SQL Databases, Workflow Management Systems, Scripting, AWS Lambda, AWS Glue, Amazon Redshift - **Published:** October 9, 2026 - **Apply:** https://www.disabledperson.com/jobs/75926189-data-quality-engineer ## About the Role We are looking for a highly talented and self- motivated Data Quality Engineer to join us on our journey in advancing the technological world through innovation and creativity., * Deep proficiency in AWS data and storage services like Amazon S3, AWS Glue, Amazon Redshift, and AWS Lambda. * Advanced proficiency in Python for building automation frameworks and orchestrating data tests. * Experience with orchestration tools (e.g., Apache Airflow), data transformation, and data quality monitoring frameworks (e.g., Amazon Deequ). * Strong command of SQL and UNIX/Linux scripting for querying and analyzing large-scale, distributed datasets Certifications: Candidate with AWS Certified Data Engineer - Associate - Highly preferred ## Description * Develop automated scripts to validate source-to-target data movements, ensuring schema consistency, completeness, and timeliness. * Build robust, reusable testing utilities using Python, native AWS services that integrate seamlessly into DataOps workflows. * Set up continuous data drift monitoring, schema validation, and data quality dashboards to proactively catch pipeline failures. * Partner with data engineers, BI teams, and software engineers to translate business rules into strict data quality KPIs and SLAs.