Director of Data Analytics

About the Role
A leading, large-scale digital media organization is seeking a Director of Analytics Strategy to join its centralized data function. This role will focus on building and operationalizing the analytics layer that supports identity resolution, audience strategy, and data product development across a diverse portfolio of digital and content-driven platforms.
You'll partner closely with Product and Engineering to ensure audience definitions, analytics systems, and data outputs are scalable, standardized, and embedded into core business workflows.
This is a highly cross-functional role sitting at the intersection of analytics, product, and data strategy. You'll translate business needs into durable analytics solutions - including reusable data models, semantic layers, and audience frameworks - enabling data-driven decision-making across the organization.
Hybrid role based in New York City, reporting into senior analytics leadership.

Key Responsibilities

• Operationalize Audience & Identity Data:
  Partner with Product and Engineering to translate audience and identity initiatives into scalable analytics systems. Define standardized business concepts and ensure they are consistently applied across reporting and data products.
• Build Scalable Analytics Infrastructure:
  Design and implement data models, dashboards, and semantic layers that enable broad adoption and self-service analytics. Ensure strong documentation, governance, and usability across teams.
• Drive Audience Insights & Measurement:
  Develop frameworks to measure performance and adoption of identity and audience initiatives. Establish KPIs, reporting standards, and benchmarks to inform targeting and growth strategies.
• Enable Cross-Functional Alignment:
  Act as the bridge between analytics, product, and engineering teams - aligning on definitions, metrics, and data requirements while promoting best practices in governance and documentation.
• Support Future Data & AI Initiatives:
  Structure data to support personalization, machine learning use cases, and automated decisioning across digital platforms.

Qualifications

• 7-10 years in analytics, BI, data strategy, or product analytics
• Strong SQL skills and experience with large-scale data warehouses (e.g., Snowflake, BigQuery, Redshift)
• Experience building identity systems, semantic layers, or scalable analytics/reporting frameworks
• Hands-on with modern data tooling (e.g., dbt, Airflow, Dagster or similar)
• Proven ability to partner with Product & Engineering to translate business needs into technical solutions
• Exposure to machine learning use cases and data structures supporting personalization or predictive modeling
• Strong communication skills - able to translate complex concepts to non-technical stakeholders
• Experience within digital, media, or consumer-facing data environments is a plus