# Director, Data Engineer (Python, Pyspark, MLOPs, LLMOPs, SQL, Databricks) at Gartner

AI Level 3, AI centrality 62 out of 100. Gurgaon.

## Details

- Company: [Gartner](https://jobsbylevel.com/companies/gartner)
- AI level: AI Level 3 (score 62 out of 100)
- Location: Gurgaon
- Posted: October 7, 2026
- Apply: https://jobsbylevel.com/go/ba9c57e6-c6b0-4ecb-8972-adc291b4e02b

## Description

About this role: 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. We are building Gartner's next generation of analytical platforms, transforming how we generate insights by moving from artisanal research to a continuous, AI-powered insight engine. This is a strategic leadership role designed for a builder who wants to leave a lasting architectural footprint. You will not be inheriting a legacy maintenance project; you will be architecting the destination state for our data, analytics, and MLOps platforms. Partnering with cross-functional leaders, you will help evolve our operating model, establishing the engineering systems, telemetry, and automated evaluation frameworks necessary to scale complex AI workflows across the enterprise. If you are looking to step up, shape a modern engineering culture, and build combinatorial AI models that will influence the high-tech industry, this is your platform. What you will do: 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 What you will need: 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. Who you are 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

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Source: https://jobsbylevel.com/jobs/director-data-engineer-python-pyspark-mlops-llmops-sql-databricks-at-gartner-b96afd

## Cite this page

Level. https://jobsbylevel.com/jobs/director-data-engineer-python-pyspark-mlops-llmops-sql-databricks-at-gartner-b96afd.

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