Lead Software Quality Assurance Engineer (Hybrid - Flexible Options)

About the Role

Key Responsibilities

• Lead QA activities for Data Pipelines, owning end-to-end automation test strategy, planning, and execution.
• Mentor and guide QA automation engineers and ensure best practices are established and followed.
• Collaborate closely with Data Engineers, Product Managers, DevOps, and business stakeholders.
• Design, develop, and maintain automated QA frameworks using PyTest, Robot Framework, JUnit/TestNG, or similar tools.
• Create and execute high-coverage, maintainable automated test cases for data pipelines and ETL processes, including Apache Airflow DAGs, AWS Glue, and custom Python/SQL test harnesses.
• Develop automated test cases for cloud and warehouse services such as AWS S3, Lambda, and Snowflake Datawarehouse.
• Conduct API testing using Postman, RestAssured, and SoapUI for RESTful APIs and integrations.
• Perform UI and BI testing for PowerBI dashboards and data visualizations using Selenium.
• Implement and manage data validation and data testing processes with QuerySurge and dbt tests.
• Develop and maintain file-based integration tests for formats such as CSV, Parquet, and JSON.
• Implement and sustain monitoring, alerting, and notification systems using AWS CloudWatch, SNS, PagerDuty, and Slack/email automation.
• Manage source code and automation workflows using Git, Jenkins, GitHub Actions, or similar CI/CD tools.
• Write and maintain scripts using Python (preferred), SQL, Bash, or similar scripting languages.
• Validate ETL/ELT processes and ensure data accuracy, completeness, and consistency.
• Design and implement automated data validation checks, reconciliation routines, and anomaly detection.
• Implement CI/CD pipelines for test automation.
• Analyze test results, provide actionable insights, and drive root cause analysis of defects.
• Ensure effective alerting and notification mechanisms for quality issues across the platform.
• Advocate for improvements in testability, automation, and data quality controls.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 7+ years of experience in QA, with at least 3 years leading QA/testing teams (preferably in the data platform space).
• Experience with AWS Cloud services such as S3, Lambda, and Glue.
• Proficiency with Snowflake, including SQL scripting and data validation.
• Experience with Apache Airflow, including DAG orchestration and test automation hooks.
• Knowledge of PowerBI, including data validation and BI automation testing.
• Experience with file integration testing for formats like CSV, Parquet, and JSON.
• Experience with API testing tools such as Postman, RestAssured, etc.
• Familiarity with CI/CD tools like Jenkins, GitHub Actions, or similar.
• Programming and scripting skills in Python (preferred), SQL, Bash, or similar languages.
• Experience with monitoring, alerting, and notification tools such as CloudWatch, SNS, PagerDuty, email, or Slack alerts.
• Strong knowledge of QA methodologies: functional, regression, integration, performance, and UAT.
• Ability to communicate clearly and collaborate with cross-functional teams.
• Self-driven with strong analytical, organizational, and problem-solving skills.

Nice to Have

• Experience with DataOps or similar data platform operational practices.
• Familiarity with data governance, security, and compliance in cloud data platforms.
• Knowledge of data test automation tools such as Great Expectations, dbt tests, QuerySurge.
• Certifications such as ISTQB, AWS, or Snowflake.

Benefits & Perks

• The salary range for this position is between $130,000 - $160,000.
• Bonus eligibility.
• Benefits information available at www.broadridgebenefits.com.