Automation Test Lead/Manager(Playwrite/Tosca and ETL Testing)

Job Title: Automation Test Lead/Manager

Skills: Test Management, Automation Testing (Playwright/Selenium/TOSCA), Snowflake (SQL validation, ETL/pipeline reconciliation), Test Strategy, Data Validation, etc

Experience: 12+years

Hiring Type: Video Interview

Job Type: Long Term

Job Location: Houston, TX (Day One Onsite Job)

NOTE: Locals are highly recommended.

Role Summary This role owns delivery for a QA managed services organization supporting a Sustainability Energy Trading and Risk Management (ETRM) platform. The person in this seat runs a multi-project team spanning functional testing, automation, and data validation, and is accountable for SLAs, quality metrics, staffing, and client governance across the account. The role blends people leadership, hands-on technical direction across automation and data platforms, and domain depth in energy/sustainability trading and emissions workflows.

• Delivery and people leadership - SLAs, governance cadence, staffing, escalations
• Automation testing - Playwright/Selenium/TOSCA, CI/CD, API validation
• Snowflake - SQL validation, ETL/pipeline reconciliation
• Power BI - dashboard and report accuracy validation tied back to Snowflake data
• Sustainability ETRM domain - trade/position/settlement concepts plus emissions and ESG reporting workflows

Delivery & People Leadership

• Run a QA managed services organization covering functional testing, automation, and data validation practice areas.
• Own commitments and SLAs, staffing and capacity planning, budgets, and quality standards for the account.
• Run the governance cadence: weekly project reviews with leads, monthly quality/metrics reviews, and quarterly business reviews with client stakeholders.
• Track defect leakage, test coverage, automation pass rates, and cycle time; act on adverse trends before they become client escalations.
• Own escalations end-to-end, from first signal through root cause and corrective action plan.
• Forecast staffing demand a quarter ahead and reallocate people across projects as priorities shift.
• Support presales and scope expansion with effort estimates, staffing models, and test approach.

Automation & Test Strategy

• Set technical direction for automation and continuous testing across the portfolio.
• Own test strategy, test planning, test case design, test data setup, defect management, and configuration management.
• Maintain and grow automated regression coverage using tools such as Playwright, Selenium, and/or TOSCA.
• Run performance, load, and non-functional testing (e.g., JMeter) where required.
• Validate REST/SOAP APIs and integrate automated checks into CI/CD pipelines (Jenkins, GitHub Actions).
• Manage source control, branching, and pull request workflows in GitHub.
• Work with AWS-hosted environments for test execution and data validation (e.g., S3, EC2, Lambda, or equivalent services depending on the platform's architecture).

Data Validation: Snowflake & Power BI

• Write and review SQL-based validation queries against Snowflake to confirm data accuracy, completeness, and consistency across source and downstream systems.
• Validate ETL/ELT pipelines feeding Snowflake, including reconciliation between source systems and the warehouse.
• Review and validate Power BI reports and dashboards for data accuracy, ensuring metrics tie back to underlying Snowflake data.
• Design and enforce value-level and null checks across data pipelines, not just field-existence checks.

Domain: Sustainability & ETRM

• Apply working knowledge of Energy Trading and Risk Management (ETRM) concepts: trade capture, positions, settlements, and risk reporting.
• Understand sustainability and emissions-reporting workflows (e.g., emissions monitoring, carbon accounting, ESG data flows) well enough to define acceptance criteria and test coverage without handholding from subject matter experts.
• Translate business and regulatory reporting requirements into test scenarios that catch real data and calculation errors.

AI-Assisted Testing

• Set standards for how AI coding/testing tools are used in delivery: what can be AI-generated, what always requires human review, and what stays off the tools entirely.
• Own quality checks on AI-generated test artifacts to ensure they validate actual business logic and data correctness.