SDET Manager

This job is with S&P Global, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

About the Role:

Grade Level (for internal use):
11  The Team:
The Quality Engineering team is at the forefront of leveraging AI technologies to enhance the quality and efficiency of our product delivery. In partnership with various Technology Functions and the Business, the team operates in an Agile environment and is globally distributed. The team is responsible for driving decisions that continuously improve customer experience and operational efficiency through innovative AI-driven solutions.
The Impact:
As an SDET Manager, you will lead and scale engineering-driven quality practices, defining and implementing AI-enabled test automation frameworks across Web, Data, API, and Services platforms. You will be responsible for driving intelligent test optimization strategies that improve automation efficiency, reliability, and coverage, while significantly reducing time to market. The role requires close collaboration with software engineers, architects, and product teams to embed quality into the development lifecycle.

You will leverage advanced technologies and data-driven insights to guide automation standards, mentor SDET teams, and ensure the delivery of high-quality, scalable software solutions.
What's in it for you:
o
Collaborate with a team of highly skilled, ambitious, and result-oriented professionals focused on AI advancements.
o
Utilize cutting-edge AI technologies to innovate testing methodologies and enhance automation.
o
Experience a dynamic environment that allows you to think and act like a developer while fulfilling QA responsibilities.
o
Engage in a culture that promotes urgency and proactive approaches in quality assurance.
o
Opportunities for skill enhancement, knowledge sharing, and innovation in AI-driven testing solutions.
o
Build a rewarding career with a global leader in financial technology.
Responsibilities:
o
Lead the design and development of test optimization solutions, ensuring alignment with organizational standards for reliability, scalability, reusability, and long-term maintainability of automated regression suites, with emphasis on data pipelines and database systems.
o
Define and oversee the implementation of AI algorithms to analyse complex testing scenarios, optimize test coverage, reduce execution time, and improve overall testing efficiency, including data quality automation across ETL/ELT pipelines.
o
Own the end-to-end test strategy, including creation and approval of test plans, test cases, and execution approaches based on functional and technical specifications, with clear analysis and executive-level reporting of results, especially for data platforms such as Databricks, Azure, and AWS.
o
Partner with data engineering and analytics teams to implement data quality checks within ETL/ELT pipelines and ensure early detection of issues
o
Provide technical leadership, mentorship, and hands-on guidance to QA and automation engineers, fostering skill development and consistent adoption of best practices in data quality assurance.
o
Review, approve, and govern team deliverables, including automation scripts, expected results, and defect documentation, ensuring quality, consistency, and adherence to timelines, particularly for data and analytics platforms.
o
Drive testing solutions across Web, API/Services, Database, and Data Pipeline layers, contributing to Agile ceremonies, project scoping, estimation, and technical design reviews.
o
Lead requirements and design reviews, advocating AI-driven testing strategies, testability improvements, and risk-based quality approaches for data-centric applications.
o
Oversee functional, system, regression, and data quality testing activities, leveraging AI-enhanced methodologies to improve effectiveness and predictability of releases.
o
Define, track, and analyse QA metrics and KPIs, translating data into actionable insights for continuous process and quality improvement, with a focus on data quality and integrity.
o
Perform effort estimation, capacity planning, and quality risk assessment, proactively identifying risks and implementing mitigation strategies to ensure predictable delivery of data solutions.
o
Drive automation of ongoing data quality checks and validation processes to ensure continuous monitoring and improvement of data integrity across platforms.

What We're Looking For:

o            8+ years of professional experience in software testing and/or development, with deep expertise in test strategies, automation frameworks, coding, and advanced debugging practices, particularly in data systems and database testing.
o
Expert-level proficiency in SQL, including complex query design, performance tuning, and advanced database interactions across platforms such as Databricks, Azure SQL, and AWS RDS.
o
Strong to expert Python programming skills, with demonstrated experience in building…