Data Platform Senior Director, Zynga

• 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 semantic/metrics layers and self-serve analytics (dbt, metrics stores, Tableau/Lightdash) and familiarity with experimentation platforms and data privacy/compliance frameworks
• Cross-functional leadership: Comfort managing non-engineering functions (Product and Production) and translating technical concepts into clear business value for executives and non-engineers

Desirable

• 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