Must Have Technical/Functional Skills
- Playwright-Centric UI & Backend Automation Leadership (Core Expectation)
- AI-Driven Quality Engineering (Strategic Expectation)
- Azure, DevOps & Platform Enablement
- Data Quality & Backend Validation
- Principal-Level Leadership & Influence
- Domain Experience (Strong Advantage)
Experience Profile
- 10+ years in SDET / Test Automation / Quality Engineering.
- Demonstrated Principal-level influence across platforms, teams, and architecture decisions.
- Deep hands-on experience designing and scaling Playwright-based automation frameworks.
- Proven experience integrating AI-assisted capabilities into modern test frameworks.
Roles & Responsibilities
About the Role
We are seeking a Principal Software Development Engineer in Test (SDET) to lead and modernize quality engineering across UI, API, services, and data layers, with a strong emphasis on Playwright-based and AI-enabled automation frameworks.
This is a hands-on technical leadership role responsible for:
- Defining next-generation automation standards.
- Building scalable, resilient Playwright-first test frameworks.
- Enabling continuous testing in Azure DevOps.
- Embedding AI-assisted and agent-driven quality practices across teams.
You will partner closely with Engineering, Product, DevOps, and Business stakeholders to drive quality by design, reduce production risk, and enable high-confidence releases in complex, data-driven systems—preferably within wealth management or financial services environments.
Data Quality & Backend Validation (Core Expectation)
- Lead the design and automation of data quality validation frameworks across:
- Databases
- Data pipelines
- System-to-system integrations
- Validate and automate checks for:
- Data completeness, accuracy, consistency, and reconciliation
- ETL / ELT transformations
- Batch jobs, scheduled processes, and file-based integrations (CSV / JSON / XML)
- Build reusable data validation utilities using SQL and Python / Java.
- Implement automated reconciliation for financial or transactional data where applicable.
- Integrate data quality tests into CI/CD pipelines or scheduled automation runs with actionable reporting.
- Proactively identify data anomalies and quality risks before production releases.
Azure, DevOps & Platform Enablement
- Drive quality engineering practices within Azure environments.
- Design and govern test execution strategies in Azure DevOps.
- Define test stages, quality gates, and reporting standards across pipelines.
- Ensure traceability across requirements, tests, defects, and releases.
AI-Driven Quality Engineering
- Champion the use of AI-assisted tools (GitHub Copilot, Copilot agents, AI assistants) to:
- Accelerate test case generation.
- Improve automation code quality and maintainability.
- Analyze test failures, logs, and quality trends.
- Define guardrails and best practices for responsible AI usage in QA.
- Drive adoption of AI-enabled productivity patterns across QE teams.
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