Senior Lead Quality Engineer

S&P Global•Princeton, NJ

3d•$120,000 - $150,000•Hybrid

About The Position

S&P Dow Jones Indices is hiring a Lead Quality Engineer for its globally distributed Quality Engineering team, which partners with Technology Functions and the business to deliver high-quality products in a SAFe Agile environment. The role contributes to testing applications across web, Windows, mobile, API, and service platforms, and to developing efficient data-comparison methods. The position focuses on reducing time to market without compromising quality through automation and innovation, while collaborating with internal teams and supporting continuous improvement in customer experience, revenue growth, and operational enablement. The successful candidate will operate independently as part of an agile team and advocate for testing best practices. They will plan and execute functional, regression, integration, and performance testing; build and maintain automated test suites for CI/CD pipelines; conduct manual testing of web and API applications; validate data using SQL; investigate and track defects; and support stakeholders with QA processes and tools. The engineer will also apply AI-powered tools and assistants to improve test design, automation, defect analysis, root-cause investigation, and QE productivity. The role is based in New York City, NY, or Princeton, NJ, with two days per week onsite. It is open only to candidates with indefinite right to work in the United States. The stated base salary range is $120,000–$150,000, with eligibility for an annual incentive plan and additional company benefits.

Requirements

At least 8 years of experience in complete software testing activities.
Strong knowledge of SDLC and STLC.
Technical proficiency with automation tools and technologies such as Java, Selenium, JUnit, TestNG, Cucumber, and Python.
In-depth knowledge of SQL for data manipulation, querying, and validation.
Experience with API testing tools such as Postman and RestAssured.
Experience using Linux operating-system command-line tools.
Excellent analytical and problem-solving skills, with attention to detail.
Strong communication and interpersonal skills and ability to collaborate effectively with cross-functional teams.
Experience supporting test-strategy activities, particularly integration of multiple applications and systems.
Ability to proactively resolve issues and escalate appropriately.
Experience testing web-based and API-based systems for user-experience issues.
Demonstrated AI fluency, including use of AI-powered tools and Agentic AI/GenAI assistants for QA work.
Bachelor’s degree in Computer Science, Engineering, or a related field.
Indefinite right to work in the United States.

Nice To Haves

Familiarity with Agile methodologies and CI/CD pipelines.
Experience with indices, benchmarks, asset management, or portfolio investment modeling.
Experience with market data in asset classes such as equity, commodity, forex, or options.

Responsibilities

Operate independently as part of an agile team and advocate for software testing best practices.
Develop and execute test plans, test cases, test scripts, and test summaries covering functional, regression, integration, and performance testing.
Collaborate with developers, product managers, and business analysts to understand requirements, identify test scenarios, and align testing with business objectives.
Design, develop, and maintain automated test suites for continuous integration and deployment pipelines.
Perform manual testing of web-based and API-based applications, including complex scenarios and edge cases.
Analyze and troubleshoot issues, defects, and discrepancies; document and track them through resolution using issue-tracking systems.
Develop and maintain SQL queries for data validation and verification.
Provide stakeholders with technical support and guidance on QA processes, tools, and methodologies.
Stay current with industry trends and emerging technologies and incorporate relevant knowledge into QA practices.
Use AI to accelerate test case development and maintenance.
Leverage AI-powered tools and Agentic AI/GenAI assistants to improve test design, test automation, defect analysis, root-cause investigation, and overall QE productivity.