Overview

As a Director of Data Engineering in the Tech Market Economics team, you will serve as a core engineering leader for a rapidly growing capability, operating with the agility of a startup but with the backing and scale of Gartner.

Responsibilities

• Architect the destination state for high-volume data pipelines that support both model training and complex, multi-prompt inference workflows at enterprise scale
• Design robust evaluation frameworks, guardrails, and automated quality gates to manage consistency, reliability, and variance in non-deterministic AI outputs
• Establish MLOps/LLMOps practices and system telemetry to monitor pipeline health, detect data and model drift, and ensure continuous performance in production
• Partner with Data Science, Product, and Research leaders to define technical roadmaps, moving prototype models into scalable, production-grade capabilities
• Architect solutions for data isolation, metadata management, and data classification across internal, external, and unstructured data sources
• Establish engineering standards, reusable code design principles, and CI/CD governance frameworks that accelerate engineering velocity while reducing technical debt
• Lead the modernization of production data platforms, identifying architectural bottlenecks, improving system resilience, and expanding end-to-end automation
• Experience: 9+ years of progressive experience in data engineering, advanced analytics, MLOps, and complex distributed system architecture.
• Education: Bachelor’s degree required; Master’s degree preferred in Computer Science, Data Science, Software Engineering, or a related quantitative discipline.
• Pipeline Architecture: Expertise in designing and optimizing robust enterprise pipelines, data workflows, and modern orchestration frameworks for complex AI/ML systems.
• AI/MLOps & Deployment: Proven track record of deploying, monitoring, and scaling AI models in production, including experience managing output consistency and implementing automated regression/evaluation suites.
• Cloud & Infrastructure: Hands-on experience architecting scalable data systems within major cloud environments and modern enterprise data platforms.
• Programming & Tooling: Strong proficiency in Python, with deep experience using numerical processing, orchestration, and automated testing libraries to develop scalable enterprise solutions.
• Quality & Telemetry: Proven ability to build evaluation tooling, system monitoring dashboards, and alerting frameworks to catch performance degradation in production.

Qualifications

• A strategic technical builder who drives enterprise value by creating scalable systems, reusable assets, and durable architectures rather than just executing isolated tasks.
• An exceptional problem solver capable of taking loosely defined requirements or prototype models and translating them into actionable engineering architecture.
• Data-driven and analytically curious, with a passion for enterprise technology markets and the role AI plays in creating combinatorial insights.
• Thrives in a fast-paced, high-growth environment, balancing multiple priorities while effectively managing risk, technical debt, and architectural trade-offs.
• An effective communicator and technical leader capable of translating complex architectural concepts, system behaviors, and MLOps methodologies to diverse business, research, and technical audiences.
• Competitive salary, generous paid time off policy, charity match program, Group Medical Insurance, Parental Leave, Employee Assistance Program (EAP) and more!
• Collaborative, team-oriented culture that embraces diversity
• Professional development and unlimited growth opportunities