Job Summary

We are seeking a Senior Data Quality Assurance Automation Engineer to help drive quality across our enterprise data lake platform. In this role, you will design and implement scalable testing and data quality frameworks, collaborate with cross-functional teams, and leverage automation and AI-assisted engineering practices to improve efficiency and reliability. We welcome candidates with diverse backgrounds and experiences who are passionate about quality engineering, data excellence, and continuous improvement.

Responsibilities

- Design and maintain automated testing frameworks for APIs, applications, data pipelines, and cloud-based services.
- Ensure data quality through data validation, profiling, reconciliation, monitoring, observability, and automated quality controls.
- Establish and improve testing standards by defining quality metrics, best practices, and testing processes across platforms.
- Leverage AI tools to improve engineering efficiency through test case generation, documentation, code reviews, and synthetic test data creation.
- Build automation solutions including internal tools, CI/CD processes, dashboards, and workflows that improve reliability and scalability.
- Apply modern engineering practices using Python, Node.js, SQL, APIs, microservices, distributed systems, and cloud platforms such as AWS, Azure, or GCP.




- Work with modern data platforms including data lakes, data warehouses, Databricks, Spark, Kafka, Delta Lake, Looker, or similar technologies.
- Collaborate with global teams and provide reasonable overlap with U.S. business hours. Experience in regulated industries and Infrastructure as Code tools (Terraform, CloudFormation) is a plus.

Requirements

- Experience in test automation, quality engineering, software testing, data quality, or related areas supporting complex applications and data platforms.
- Strong automation experience, including CI/CD pipelines and tools such as Jenkins, GitLab CI, GitHub Actions, Airflow, or similar technologies.
- Proficiency in Python, Node.js, SQL, or similar programming languages.
- Experience implementing data quality practices, including data validation, profiling, reconciliation, monitoring, and automated quality controls.
- Understanding of APIs, microservices, backend systems, and up-to-date software architecture principles.
- Experience working with cloud platforms such as AWS, Azure, or GCP, and distributed systems.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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