Lead QA Automation Engineer

This is a fully remote position, open to applicants in Illinois.

📋 Description

• Oversee small to medium-sized QA projects, establishing testing strategies, automation plans, and execution roadmaps.

• Collaborate with business and IT stakeholders to convert data requirements into testable scenarios.

• Create, develop, and sustain test automation frameworks and quality engineering architectures for big data platforms.

• Conduct testing and validation of data models, pipelines, transformations, and repositories/catalogs.

• Construct and maintain automated validation of data ingestion from source systems into the data lake.

• Guide and mentor QA engineers, promote best practices, and take responsibility for team quality outcomes.

• Generate test coverage models, data validation schematics, and capacity-aware testing strategies.

• Enhance test automation efficiency, data validation performance, and security validation processes.

• Set up quality metrics, KPIs, and monitoring frameworks.

• Suggest and uphold QA standards, automation frameworks, and testing protocols across data platforms.

⛳️ Requirements

• Bachelor’s Degree in Arts/Sciences (BA/BS) or equivalent education/experience — Required.

• Master’s degree in Arts/Sciences (MA/MS) — Preferred.

• 8+ years of experience in big data or a related field — Required.

• 8+ years of expertise in cataloging, modeling, ingestion, processing, and streaming technologies and processes — Required.

• 4+ years of experience in Data Analysis — Required.

• Ability to lead QA teams, drive automation strategies, and influence stakeholders across functions.

• Strong problem-solving and analytical capabilities for validating complex data scenarios.

• Proficiency in data testing, including ETL, data pipelines, data lake validation, and reconciliation.

• Skilled in SQL and data validation methodologies, including checks for completeness, accuracy, and lineage.

• Comprehensive understanding of CI/CD pipelines and the integration of automation.

• Experience in validating data quality rules, transformations, and business logic across data layers.

• Knowledge of data security, privacy (PII), and compliance validation requirements.

• Preferred experience in API and integration testing using REST, JSON, and data contracts.

• Preferred hands-on experience with Playwright, Selenium, or Cypress.

• Preferred familiarity with Hive, Spark, NoSQL, and data lake architectures.

• Preferred experience in data warehouse/BI testing.

• Preferred knowledge of Azure, AWS, Snowflake, or Databricks.

• Preferred exposure to data observability, monitoring, and quality control frameworks.

• Preferred experience in implementing test metrics, KPIs, and quality dashboards.

• Preferred understanding of performance testing for data pipelines.

🏝️ Benefits

• Annual bonus plan.

• Eligibility for long-term equity incentive plans for select positions.

• Comprehensive health, retirement, and other employee benefits.

• A respectful and welcoming work environment.

• Opportunities for career advancement and global prospects.