At Q4, we make an impact together, obsess over our customer, operate with integrity, and bring big ideas to life.

Q4 is charting a bold new path for investor relations as the first AI-driven IR Ops Platform, providing everything an IR team needs to succeed on a single, powerful platform. The Q4 Platform enables public companies to attract, manage, and understand investors - all in one place. Over 2,600 customers, including many of the most respected brands in the world, trust Q4 to help drive premium valuations for their companies. Only Q4 offers a tech stack holistically designed to equip IR teams with data, insights, and smart workflows that power remarkable outcomes. Learn more at q4inc.com.

We hire smart, curious, and talented people to push boundaries, reimagine what’s possible, and turn challenges into opportunities. All while keeping the needs of our clients at the heart of everything we do.

Come grow with us!

About the role

The Data QA Engineer will drive adoption of AI-powered tools and intelligent automation to enhance testing efficiency, coverage, and defect detection throughout the software development life cycle. Provide data governance, quality leadership, and guidance to the Data team, while advocating for measurable improvements in product quality through modern QA practices.

What you'll do

• Leverage AI-powered tools and generative AI to automate test case generation, prioritize high-risk scenarios, and minimize manual effort.
• Implement intelligent automation (e.g., self-healing tests, AI-driven anomaly detection) to enhance test reliability and speed.
• Research and integrate emerging AI tools to streamline data validation, regression testing, and quality reporting.
• Collaborate with the team to evolve testing toward highly automated, AI-augmented processes.
• Ensure end-to-end data integrity and completeness validation across pipelines.
• Conduct gap analysis, data mapping, process documentation, and flow charting.
• Enforce quality control for all software deliverables and elevate QA standards/best practices.
• Deliver actionable insights and sprint quality reports; drive retrospective discussions for continuous improvement.

Tasks

• Use AI tools (generative AI, intelligent platforms) to auto-generate/maintain SQL queries, test scripts, and validation scenarios.
• Build and maintain advanced Python-based automated test suites with AI for smarter selection, flaky test detection, and coverage optimization.
• Experiment with AI-assisted root cause analysis for data issues and incidents.
• Track and report automation coverage, AI-driven efficiency gains, defect trends, and sprint quality metrics.
• Create, execute, and maintain tests targeting data completeness, integrity, and pipeline health.
• Act as primary QA contact at squad level; participate in all sprint rituals and facilitate retro discussions.
• Conduct regular syncs with interns, Development Lead, and Product Owners.
• Maintain comprehensive test suites, documentation, and quality artifacts.
• Drive resolution of production incidents (SUPIN/RCA exercises)

Qualifications

• 3+ years in a data quality or QA engineering role in software development.
• Proven experience with AI-powered testing tools (e.g., Testim, Mabl, Applitools, Functionize, CodiumAI etc) to boost automation and efficiency.
• Hands-on use of generative AI (ChatGPT, Copilot, LLMs) for test case/script generation, scenario creation, or defect analysis.
• Strong background in intelligent/self-healing test automation frameworks.
• Familiarity with AI-assisted data validation (e.g., anomaly detection, predictive prioritization).
• Experience automating ETL/ingestion pipeline testing; financial data is a strong plus.
• Expert SQL for data manipulation and validation.
• Proficiency in Python for test automation and streamlining processes.
• Solid data exploration and analysis skills using relevant tools.
• Deep knowledge of Agile, CI/CD, QA methodology, and processes.
• Hands-on with bug tracking and test management tools (JIRA, TestRail).
• Experience on fast-paced agile product teams.
• Excellent written and oral communication.
• Comfortable in dynamic environments with frequent change.
• Passion for continuous learning and adopting latest QA tools/practices.

Compensation & Pay Transparency: The anticipated compensation for this role is R$ 200,000 – R$ 240,000 BRL per year (Gross). Final compensation is determined by a candidate's unique skills, experience, and internal equity

Vacancy Status: This job posting is for an existing vacancy currently open at Q4.

Artificial Intelligence (AI) Disclosure: In our commitment to an efficient and objective hiring process, Q4 utilizes machine-based systems (AI) to assist in the initial sourcing of applicants. All final hiring and selection decisions are reviewed and conducted by our human recruitment team.