Senior Data Product and Governance Specialist

Senior Data Product & Governance Specialist based in Washington, DC. In this pivotal role, you will bridge the gap between technical data engineering and enterprise strategy by developing, validating, and maintaining the analytical assets that power a massive information ecosystem. You will act as a Client of data integrity, implementing sophisticated governance frameworks and metadata standards to ensure that data products—ranging from datasets to AI models—are reliable, explainable, and ethically sound. This is a high-impact opportunity for a professional who thrives on transforming complex data into a trusted corporate asset while navigating the evolving landscape of AI and automated decision-making.

Key Responsibilities

• Asset Development: Design, build, and operationalize high-quality data products, including datasets, metrics, and models that support enterprise-wide decision-making.
• Governance & Ethics: Define and apply data and AI governance policies, ensuring all outputs align with compliance, risk management, and ethical standards.
• Metadata Management: Configure and manage enterprise metadata and catalog platforms, maintaining automated lineage and consistent glossary alignment across cloud and ERP environments.
• Quality Assurance: Establish and monitor rigorous data quality standards, access controls, and model risk oversight to ensure "trusted" analytical outputs.
• Transparency & Lineage: Document and maintain comprehensive metadata and interpretability information to strengthen data transparency for stakeholders.
• Cross-Functional Collaboration: Partner with agile teams to integrate analytical assets into operational workflows and continuously improve data integration processes.

Qualifications

• Education: Bachelor’s degree in Data Science, Computer Science, Information Systems, Statistics, or a related technical field.
• Professional Experience: 2–4 years of experience in data, analytics, or AI-related roles, with a specific focus on governance, stewardship, or metadata management.
• Technical Proficiency: Proven ability to design and validate analytical logic and translate complex business terminology into structured metadata standards.
• Governance Knowledge: Strong understanding of data/AI governance principles, including stewardship models, quality thresholds, and responsible data use.
• Strategic Thinking: Exceptional analytical and diagnostic skills with the ability to turn findings into actionable process improvements.
• Agile Expertise: Experience contributing to iterative product delivery within an agile framework.
• AI Familiarity (Preferred): Knowledge of AI ethics, prompt development, or model validation concepts is highly desirable.