Back
Tier-1 brand plus metro location but senior, specialized QA reduces applicant density.
Requires deep data platform and automation expertise, limiting transferability across industries.
Multiple mandatory automation, cloud, and data-platform skills required without explicit years.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and maintain automated testing frameworks and data quality controls for APIs, applications, data pipelines, and cloud services.
Ensure data quality through validation, profiling, reconciliation, monitoring, and observability of enterprise data lake platform.
Build automation solutions including CI/CD pipelines, dashboards, and leverage AI tools to improve engineering efficiency and testing coverage.
Experience in test automation, quality engineering, software testing, or data quality for complex applications and data platforms.
Strong automation skills with CI/CD tools such as Jenkins, GitLab CI, GitHub Actions, or Airflow.
Proficiency in programming languages like Python, Node.js, and SQL.
Experience working with cloud platforms (AWS, Azure, or GCP) and modern data technologies like data lakes, Databricks, Spark, Kafka, Delta Lake, or similar.
Experienced in building and scaling automated testing frameworks for data and cloud platforms in a global team environment.
Proficient in integrating modern software architecture principles including microservices, APIs, and distributed systems.
Capable of collaborating across global teams with reasonable overlap in U.S. business hours and leveraging AI-assisted engineering practices.