Senior QA Engineer, Market Data
Intercontinental Exchange
- Location
- Hyderabad, India
- Employment
- Full Time
- Work model
- On-Site
- Level
- Senior
Skills
About this role
Job Description
Job Purpose Intercontinental Exchange, Inc. (ICE) presents a unique opportunity to work with cutting-edge technology and solve complex business challenges in the financial sector. This Senior QA Engineer role is focused on Market Data applications and plays a key role in validating high-quality, reliable market data solutions that support trading, reporting, compliance, and downstream consumer workflows. The Senior QA Engineer will be responsible for designing, executing, and improving test coverage for Market Data systems. The role requires strong domain understanding of market data workflows, feed processing, reference data, trading lifecycle impacts, and validation of data accuracy, completeness, timeliness, and downstream publishing. This position requires strong analytical skills, hands-on technical troubleshooting, excellent communication, and the ability to independently drive QA activities with minimal technical supervision. We are seeking a highly skilled Senior QA Engineer with strong experience in Market Data systems and financial markets QA. The ideal candidate will have hands-on experience validating market data feeds, reference data changes, symbol/security lifecycle events, data dissemination, and regression coverage across complex trading and market data platforms. The successful candidate will work across the Software Development Life Cycle (SDLC), partner closely with development, product, operations, and business teams, and contribute to quality delivery in a fast-paced, team-based environment. The role includes creating and executing test plans, test scenarios, and test cases; identifying and reporting defects; validating fixes; supporting production/UAT changes; and continuously improving QA processes, automation coverage, and test efficiency.
Responsibilities
Develop and implement comprehensive test plans, test scenarios, and test cases for Market Data applications, including functional, regression, integration, end-to-end, and data validation coverage. Validate market data feed processing, reference data updates, symbol/security lifecycle events, trading session behavior, and downstream data publishing to ensure accuracy and completeness. Perform detailed validation of market data outputs across environments using logs, database queries, reports, and application-level checks. Identify, document, and report software defects using Jira or equivalent defect tracking tools, and collaborate with developers and product teams through resolution and retesting. Review and triage test failures, analyze logs, isolate root cause, and verify fixes across QA, UAT, and production-like environments. Contribute to automation coverage by developing, maintaining, and executing automated tests for regression and recurring validation activities. Ensure new features, enhancements, reference data changes, and bug fixes do not negatively impact existing Market Data functionality or downstream consumers. Collaborate with cross-functional teams involved in product delivery, including development, product management, operations, support, and business stakeholders. Maintain clear and concise documentation of test plans, test cases, execution results, defect evidence, and sign-off summaries. Participate in production change support, UAT validation, issue investigation, and service restoration activities when required. Stay current with QA engineering practices, market data testing approaches, automation frameworks, and financial technology trends. Knowledge and Experience Solid hands-on experience in Market Data or related financial data systems, including validation of feed ingestion, data transformation, dissemination, reporting, and downstream consumption. Strong understanding of capital markets, trading workflows, reference data, security master concepts, symbols, instruments, sessions, and lifecycle events affecting market data behavior. Experience validating market data quality dimensions such