Quality Engineer
London Stock Exchange Group22 hours ago
Hyderābād, IndiaMid Level / Senior
Responsibilities
- Design and execute test scenarios and test cases from business and functional requirements.
- Validate ETL/ELT pipelines, data transformations, integrations, business rules, and end-to-end data flows.
- Perform data quality, reconciliation, regression, integration, and large-volume data testing.
- Develop and maintain automated test frameworks using Python, PyTest, Cucumber, or equivalent tools.
- Use SQL and Snowflake for data validation, reconciliation, and root-cause analysis.
- Integrate automated tests and quality gates into CI/CD pipelines.
- Perform deployment validation, configuration checks, log analysis, and release verification using Git-based workflows.
- Test Generative AI applications for accuracy, relevance, groundedness, consistency, hallucination risk, and guardrail effectiveness.
- Validate Agentic AI workflows, including tool and API interactions, multi-step execution, retries, error handling, and task completion.
- Create reusable test datasets and automated evaluation checks for data and AI solutions.
- Use AI-assisted methods for test-case generation, automation, defect analysis, and QA efficiency.
- Document, track, and communicate defects, risks, and quality metrics.
- Collaborate with Data Engineering, Platform, DevOps, Product, Business, and Engineering teams to improve quality and release outcomes.
Requirements
- Requires 3–7 years of experience in Data QA, ETL testing, data quality engineering, or test automation.
- Requires strong SQL skills, including complex queries, joins, aggregations, window functions, and data reconciliation.
- Requires hands-on experience with Snowflake and data warehouse or data-platform testing.
- Requires Python-based test automation experience using PyTest or a similar framework.
- Requires working knowledge of CI/CD tools such as Azure DevOps, GitHub Actions, Jenkins, or equivalent tools.
- Requires understanding of Git, branching, pull requests, deployment workflows, logging, and monitoring.
- Requires familiarity with AWS and/or Azure and modern cloud-based data architectures.
- Requires basic knowledge of Generative AI concepts including prompts, grounding, hallucinations, non-deterministic outputs, and guardrails.
- Requires basic knowledge of Agentic AI concepts including agents, tools, APIs, orchestration, and multi-step workflows.
- Requires experience working in Agile delivery environments using Jira or an equivalent work-management tool.
- Requires strong analytical, troubleshooting, communication, and collaboration skills.
- Preferred experience includes work in Financial Services or another regulated industry.
- Preferred exposure includes Infrastructure as Code tools such as Terraform, Bicep, ARM, or CloudFormation.
- Preferred knowledge includes Docker or other container technologies, cloud monitoring, and observability tools.
- Preferred awareness or experience includes Azure AI Foundry evaluations, RAGAS, DeepEval, LangSmith, and AI-assisted test generation, automation, or defect analysis.
Benefits
- Hybrid work arrangement in Bengaluru, India.
- Full-time employment.
- Healthcare benefits, retirement planning, paid volunteering days, and wellbeing initiatives.
- Personal development supported through formal and informal learning tools.
- Collaborative, creative, and inclusive culture with equal-opportunity and reasonable-accommodation commitments.
- Opportunity to work on enterprise data, cloud, DevOps automation, Generative AI, and Agentic AI assurance.
Categories
Data EngineeringTesting
About London Stock Exchange Group
London Stock Exchange Group (LSEG) provides market infrastructure, financial data, and analytics to banks, asset managers, and corporations. Its businesses span capital markets (London Stock Exchange), post-trade clearing (LCH), and information services including FTSE Russell indices and the Refinitiv data platform, funded by transaction fees, subscriptions, and licensing. Headquartered in London and publicly listed on the LSE, the group serves global customers seeking trading, clearing, benchmarks, and enterprise data solutions.