Responsibilities
Monitor and automate ETL pipelines using AWS services such as Redshift, S3, Glue, Lambda, Athena, and Step Functions.
Perform data analysis and profiling to understand data structure, quality, and transformation requirements.
Identify and resolve data quality issues through cleansing, validation, and standardization processes.
Build and maintain automation frameworks using Python, PySpark, or Cucumber to support scalable and reliable test automation.
Develop end to end automated test suites covering critical workflows, edge cases, and negative scenarios.
Integrate automated tests into CI/CD pipelines using Jenkins, GitHub Actions, or similar tools.
Conduct backend testing, including SQL validation, schema verification, and data transformation checks across AWS data stores.
Monitor data pipelines and automated workflows, troubleshoot failures, and implement robust error handling mechanisms.
Collaborate with data engineers, developers, and product teams to ensure high quality automation coverage.
Document test strategies, automation frameworks, and data validation processes while promoting automation best practices.
Skills & Experience
5+ years of experience in QA, test automation, or data engineering automation.
3+ years of experience testing data pipelines, ETL workflows, or cloud based data products.
Strong SQL skills with experience validating data in Redshift, Athena, or similar cloud data warehouses.
Hands on experience working with AWS services such as S3, Lambda, Glue, Redshift, Athena, and Step Functions.
Proficiency in Python and PySpark for automation, data processing, and framework development.
Experience with automation frameworks such as Cucumber, PyTest, Behave, or custom-built frameworks.
Experience integrating automated tests into CI/CD pipelines (Jenkins, GitHub Actions, etc.).
Familiarity with test management tools such as Jira Xray, TestRail, or similar platforms.
Strong understanding of ETL concepts, data validation, and backend testing.
Excellent attention to detail with an automation first mindset and strong debugging skills.
Healthcare technology experience is a plus.
AI experience in test automation is preferred
PREFERRED QUALIFICATIONS
Master's degree in computer science, Data Engineering, or a related field preferred but not required.
Experience with streaming data frameworks (Kafka, Kinesis, Spark Streaming).
Familiarity with advanced analytics frameworks and ML pipelines (MLflow, SageMaker, Feature Stores).
Certifications: AWS Certified Data Analytics
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