AI Data Quality Assurance Engineer

About the role

We are seeking a Data QA Engineer to ensure the quality, reliability, robustness, and trustworthiness of data-driven platforms that support analytics and reporting.

Responsibilities

• Data Quality Strategy
• Define and own data quality strategies for data-driven platforms, including pipelines, transformations, and downstream consumption layers
• Establish data quality gates covering accuracy, completeness, consistency, timeliness, and reliability
• Data Pipeline & Consumer Validation
• Design and execute tests for batch and streaming data pipelines, ensuring end-to-end data correctness
• Validate data transformations, aggregations, and reconciliations across multiple sources and consumers
• Ensure analytics, reporting, and ML inference outputs are accurate, consistent, and reproducible
• Validate data feeding LLM-based or agentic systems, focusing on inputs, outputs, and impact on core datasets
• Data Integrity & Lifecycle Validation
• Validate dataset quality across ingestion, transformation, storage, and consumption stages
• Enforce schema validation, null checks, referential integrity, and lineage tracking
• Monitor for data drift, anomalies, volume changes, and performance regressions post-deployment
• Test Automation for Data Platforms
• Build and maintain automation frameworks for data quality testing, including rule-based and statistical checks
• Integrate data quality tests into CI/CD pipelines for continuous validation
• Automate UI and service-level validations to ensure data is correctly surfaced, consumed, and represented across dashboards, reports, APIs, and downstream services
• Cross-Functional Collaboration
• Partner closely with Data Engineers, Analytics teams, Software Engineers, and Product Owners throughout the delivery lifecycle
• Provide clear, actionable feedback on data quality risks, gaps, and improvement opportunities

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical discipline or equivalent practical experience in Quality Engineering for data-driven platforms
• Strong experience in QA or Quality Engineering, preferably focused on data platforms, analytics, or reporting systems
• Hands-on experience validating data pipelines, transformations, and large-scale datasets
• Proficiency in Python (or similar languages) for data validation, automation, and testing workflows
• Solid understanding of data engineering concepts, including schema management, data quality checks, reconciliation, and lineage
• Experience integrating data quality tests into CI/CD pipelines for continuous validation
• Experience validating downstream data consumers, including analytics, reporting layers, services, or APIs
• Exposure to ML inference outputs or AI-enabled consumers, with a focus on validating data inputs and outputs rather than model internals
• Familiarity with working in regulated or data-sensitive environments, including auditability and traceability requirements
• Awareness of AI-enabled systems (e.g., LLMs or agentic workflows) where they consume or produce data is a plus, but not required

Qualifications

• Experience with test automation frameworks used for data, service, or platform validation
• Awareness of AI-enabled systems (e.g., LLMs or agentic workflows) where they consume or produce data is a plus, but not required

What We Offer

• Opportunity to work on enterprise-scale data platforms supporting analytics, reporting, and downstream ML/AI use cases
• Ownership of data quality strategy, tooling, and automation across core data pipelines
• Closer collaboration with Data Engineers, Software Engineers, Product Owners, and Analytics teams
• Exposure to data validation frameworks, large-scale datasets, and selective AI-enabled data consumers
• A mandate to define, measure, and govern data quality standards across squads and delivery teams

Why Fitch?

• A global leader in financial information services with operations in more than 30 countries
• Embraces a diverse culture that encourages a free exchange of ideas, guaranteeing your voice will be heard and your work will have an impact, regardless of seniority
• Committed to providing global securities markets with objective, timely, independent and forward-looking credit opinions
• Building incredible things at Fitch, and we invite you to join us on our journey

Base Pay Range

Expected base pay rates for the role will be between $115,000 and $130,000 per year. Actual salaries will be determined on an individualized basis and may vary based on factors including but not limited to education, training, experience, past performance, and other job-related factors.