Senior Director, Data Platform

Job description

Level Up Your Career with Zynga! At Zynga, we bring people together through the power of play. As a global leader in interactive entertainment and a proud label of Take-Two Interactive, our games have been downloaded over 6 billion times—connecting players in 175+ countries through fun, strategy, and a little friendly competition. From thrilling casino spins to epic strategy battles, mind-bending puzzles, and social word challenges, our diverse game portfolio has something for everyone. Fan-favorites and latest hits include FarmVille™, Words With Friends™, Zynga Poker™, Game of Thrones Slots Casino™, Wizard of Oz Slots™, Hit it Rich! Slots™, Wonka Slots™, Top Eleven™, Toon Blast™, Empires & Puzzles™, Merge Dragons!™, CSR Racing™, Harry Potter: Puzzles & Spells™, Match Factory™, and Color Block Jam™—plus many more! Founded in 2007 and headquartered in California, our teams span North America, Europe, and Asia, working together to craft unforgettable gaming experiences. Whether you're spinning, strategizing, matching, or competing, Zynga is where fun meets innovation—and where you can take your career to the next level. Join us and be part of the play! Position Overview: The Senior Director, Data Platform will lead Zynga's centralized data platform and product strategy, managing one of the largest data footprints in the gaming industry—billions of daily gameplay events flowing through a cloud-native stack spanning real-time ingestion, a petabyte-scale warehouse, experimentation, and a self-serve metrics and AI platform. Operating with high autonomy and direct executive sponsorship, you will act as a pathfinder: empowering our global studios to extract maximum value from central data and transforming the group to an AI-first way of working. This highly visible role is based in Toronto and partners closely with studio leaders, central teams, and executives across Zynga's global labels. Relocation support is available. What You'll Do: Craft data product strategy: Define, roadmap, and execute the product strategy for Zynga's centralized data products, translating vision into initiatives that empower global studios. Drive AI adoption: Champion an AI-first approach, pushing teams to innovate and leverage clean, trusted data for advanced AI/ML capabilities. Lead a global team: Manage, mentor, and grow a diverse team of ~60 across North America, Israel, and India—including Directors, Senior Managers, and non-engineering functions such as Product and Program Management. Oversee data governance: Establish robust data compliance and governance frameworks for a massive, global data footprint. Navigate and execute: Guide the team through organizational change while maintaining global alignment and building effective processes and outcomes. What You Bring: Experience: 15+ years in data or software engineering, including 8+ years leading and scaling engineering organizations, with experience managing managers (Directors and Senior Managers). Executive leadership: A track record leading global, matrixed teams of tenured leaders, with strong executive presence across studios, labels, and executive stakeholders. Technical pedigree: A deep engineering background—including hands-on IC experience earlier in your career—with the depth to make architectural calls across a modern cloud data stack: cloud data warehousing (Redshift, Snowflake, BigQuery), streaming (Kafka, Kinesis, Spark), orchestration and transformation (Airflow, dbt), and lakehouse/ML platforms (Databricks, SageMaker). Highly technical product leaders on the data side are also encouraged to apply. AI/ML expertise: A proven, hands-on track record of shipping AI/ML systems to production—feature/training pipelines, deployment, and monitoring. Familiarity with modern LLM and agentic patterns (RAG, semantic layers, MCP-style tooling) is a strong need. This is a critical, non-negotiable requirement. Platform depth: Demonstrated ownership of large-scale, cloud-native data platforms on AWS—modeling, batch and streaming pipelines, cost/performance optimization, reliability (SLOs, observability), and data quality at scale. Semantic layer & governance: Experience scaling semant