Director, Data Engineering – AI & Data Platforms

Company And Culture

Complex is the definitive platform for global youth culture and music lifestyle, seamlessly integrating cutting-edge content, commerce and live experiences with unparalleled scale. Through innovative content, Complex tells stories of music, streetwear and style, sports, art and beyond. Its content engages in a dynamic conversation with the audience, reflecting and shaping the zeitgeist of convergence culture. A powerful media juggernaut paired with a curated marketplace, Complex is redefining the way fans interact with their favorite brands and artists and reshaping the future of digital culture and commerce.

Why We're Hiring

We are seeking a Director, Data Engineering – AI & Data Platforms to lead the strategy, architecture, development, and evolution of our data and AI infrastructure. This is a hands‑on leadership role responsible for building a scalable, reliable, and AI‑ready data platform that powers analytics, machine learning, automation, and emerging generative AI applications.

The Director will lead the design and implementation of modern data architecture while partnering closely with engineering, analytics, product, and business stakeholders. There will be a a focus on AI initiatives, including developing the data foundations required for machine learning and generative AI, identifying opportunities for AI‑driven automation, and helping translate emerging AI capabilities into practical business applications.

This role is ideal for a technical leader who enjoys operating at both the strategic AND hands‑on levels and is comfortable building systems, establishing engineering standards, mentoring engineers, and driving cross‑functional initiatives in a fast‑moving digital media environment.

This position will be on‑site in our New York, NY or Los Angeles, CA office.

• Own the strategy, architecture, and roadmap for the company's data engineering and analytics platform.
• Design and oversee scalable, secure, and cost‑effective data architectures and pipelines supporting analytics, reporting, machine learning, and AI applications.
• Establish engineering standards for data modeling, pipeline development, testing, deployment, observability, documentation, and operational excellence.
• Lead the development and optimization of batch and near‑real‑time data pipelines using SQL and Python.
• Oversee data modeling and warehouse architecture in Snowflake, ensuring scalability, performance, reliability, and efficient use of resources.
• Drive the evolution of our cloud‑based data infrastructure using AWS, including S3, EC2, Lambda, and related services.
• Establish robust frameworks for data quality, testing, monitoring, lineage, observability, and alerting.
• Evaluate and introduce technologies that improve the scalability, reliability, and efficiency of the data platform.
• Balance hands‑on technical contribution with architectural oversight and engineering leadership.

• Lead the data engineering strategy supporting machine learning, generative AI, and AI‑powered applications.
• Partner with data scientists, engineers, analysts, and business leaders to identify and prioritize high‑value AI opportunities.
• Design and oversee data pipelines supporting model training, feature engineering, inference, evaluation, and monitoring.
• Develop the data foundations required for LLM and generative AI applications, including data preparation, embeddings, vector data, retrieval pipelines, and RAG architectures where appropriate.
• Establish processes for AI data quality, model evaluation, experimentation, and performance monitoring.
• Identify opportunities to use AI to improve internal workflows, analytics, data operations, content‑related processes,…