Senior Lead QA Engineer – Automation & AI Testing

S&P Global, Inc.

New York (NY)

Hybrid

USD 120,000 - 150,000

Full time

3 days ago

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Benefits offered by this job

Annual incentive plan

Benefits package

Job summary

S&P Global Dow Jones Indices is seeking a Lead Quality Engineer to drive automated testing across Web/Windows/API platforms. Hybrid role in NYC or Princeton with strong collaboration across technology teams.

The ideal candidate will bring 8+ years in software testing, deep knowledge of Java/Selenium and API testing tools, and experience with CI/CD pipelines. The role emphasizes AI-enabled testing and high-quality product delivery.

Qualifications

8+ years of experience in complete software testing activities.
Strong knowledge of SDLC and STLC.
Proficient in automation tools and technologies such as Java, Selenium, JUnit, TestNG, Cucumber, Python etc.
In-depth knowledge of SQL for data manipulation, querying, and validation.
Experience with API-based testing tools such as Postman and RestAssured.
Experience with Linux operating systems command-line tools.
Excellent analytical and problem-solving skills, with attention to detail.
Strong communication and interpersonal skills for cross-functional collaboration.
Experience in CI/CD pipelines and Agile methodologies.
Demonstrated skill to leverage AI fluency to improve test design and automation.
Experience with Market Data or Asset Management a plus.

Responsibilities

Be a self-starter; operate independently as part of an agile team, advocate for software testing best practices.
Develop and execute test plans, test cases, test scripts and test summaries to ensure coverage of functional, regression, integration, and performance testing.
Collaborate with developers, product managers, and analysts to understand requirements and align tests with business objectives.
Design, develop, and maintain automated test suites for CI/CD pipelines.
Perform manual testing of web, API-based applications, focusing on complex scenarios and edge cases.
Analyze and troubleshoot defects, document issues, and track to resolution.
Develop SQL queries for data validation and verification.
Provide guidance on QA processes, tools, and methodologies.
Stay updated on industry trends and AI-enabled testing approaches.
Utilize AI to accelerate test design and maintenance.