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S&P Global · 1 day ago

Director Data Quality Engineering

Princeton, NJ

Full-time

Hybrid

Director/Executive

$135K/yr - $190K/yr

15+ years exp

S&P Global is a leading provider of credit ratings and analytics, and they are seeking a Director of Data Quality Engineering. This high-impact senior leadership role involves building and scaling data and AI quality engineering across the enterprise, ensuring accuracy and compliance in data transformations, and leading a global team to drive measurable outcomes in customer trust and delivery speed.

AnalyticsBusiness IntelligenceCreditEnterprise SoftwareFinanceFinancial ServicesInformation ServicesMarket Research

Culture & Values

No H1B

Responsibilities

Build and scale the blueprint for data and AI quality engineering across the enterprise

Ensure lineage, migrations, and transformations deliver accuracy, compliance, and trust

Lead the data service team at the intersection of data, AI, customer experience, and engineering excellence

Shape the future of enterprise data quality and AI assurance, driving measurable outcomes in customer trust and delivery speed

Drive enterprise-wide QE strategy across ELT pipelines, data transformations, migrations, cataloging, and observability

Ensure AI/ML models are validated for accuracy, fairness, robustness, and compliance

Embed engineering excellence into the data lifecycle, making quality a continuous capability

Partner across data engineering, data science, product, and compliance to elevate customer experience and delivery speed

Define and execute QE strategy for Data Services, Data Science, and Core Data Platforms

Drive adoption of data lineage and cataloging frameworks for traceability and compliance

Lead quality strategies for ETL/ELT workflows, transformations, and migrations

Oversee frameworks for reconciliation, anomaly detection, and schema validation

Establish robust validation practices for AI/ML models (accuracy, fairness, transparency)

Partner with Data Science teams to ensure responsible AI through repeatable methods

Drive autonomous testing and AI-augmented QE for scalable validation

Champion observability and continuous quality in cloud-native data platforms (AWS, Azure)

Promote automation, governance, and reusable frameworks

Foster innovation via synthetic data and intelligent simulation tools

Lead and mentor a global QE team, fostering innovation and accountability

Partner with engineering, product, DevOps, and compliance leaders for end-to-end ownership

Influence cross-functional strategy with scalable frameworks and governance

Define KPIs for data quality, lineage accuracy, AI reliability, and QE maturity

Align QE practices with emerging tech, regulations, and business priorities

Deliver measurable impact in data trust, customer satisfaction, and delivery speed

Qualification

Quality EngineeringData LineageAI/ML Model ValidationJavaPythonSQLETL/ELT PipelinesData GovernanceCloud PlatformsStakeholder InfluenceAutomationContinuous QualityCross-functional Leadership

Required

15+ years in Quality Engineering, with leadership in data-centric environments

Expertise in data lineage, cataloging, governance, and observability (Collibra, Informatica, Alation)

Proficiency in Java, Python, JavaScript, TypeScript, SQL, and scripting languages for test automation and security validation

Experience with data validation, observability, test data management, and analytics platforms (e.g., Splunk, ELK, Grafana)

Proven success in ETL/ELT pipelines, transformations, and migrations

Strong knowledge of modern data platforms, including cloud-based data processing, analytics, and workflow orchestration solutions

Experience with AI/ML model testing and validation frameworks

Familiarity with synthetic data, autonomous testing, and continuous quality

Strong cross-functional leadership and stakeholder influence

Preferred

Experience in regulated industries (finance, healthcare, pharma)

Certifications in Cloud, Data Engineering, or AI/ML

Exposure to data observability and MLOps platforms

Recognized contributions to QE best practices (speaking, publishing, thought leadership)

Benefits

Health & Wellness: Health care coverage designed for the mind and body.

Flexible Downtime: Generous time off helps keep you energized for your time on.

Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills.

Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs.

Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families.

Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.