Sr. Staff Data Architect, CNN Data Analytics, Science & Insights

Warner Bros. Discovery•New York, NY

11d

About The Position

We are seeking a visionary and hands-on Sr. Staff Data Architect to join our team and play a pivotal role in shaping the future of our data ecosystem. This is a strategic leadership role responsible for designing the blueprint of our next-generation data platform. You will lead the design and evolution of our gold semantic layer, drive metrics standardization across the enterprise, and ensure our data architecture is scalable, reliable, and future-proof. You will be a technical authority and a mentor, guiding the team in building robust data models for audience segmentation, content analytics, product analytics, growth analytics, and more. If you are passionate about building foundational data systems from the ground up and want to have a massive impact on our transformation into a data-driven organization, this is the role for you!

Requirements

8+ years of experience in data engineering, data architecture, or a related field, with at least 3 years in a senior architectural role.
Deep expertise in cloud data warehousing, specifically Snowflake. You have hands-on experience with performance tuning, security, cost optimization, and data modeling strategies at scale.
Strong proficiency with the modern data stack, including hands-on experience building and orchestrating data pipelines with dbt and implementing data quality/observability with Monte Carlo or similar tools.
Experience with event data collection, ideally with Snowplow or a comparable solution. You understand the challenges and best practices for clickstream data instrumentation and processing.
Proven experience designing and building semantic layers or metric stores to create a single source of truth for business intelligence.
Strong understanding of how to architect data models for optimal consumption in BI tools. You are proficient with platforms like Looker, Tableau, or Domo, and can translate business reporting needs into efficient and scalable data structures
Exceptional strategic thinking, communication, and presentation skills. You can articulate complex technical concepts to non-technical stakeholders and build consensus around a long-term vision.
A builder's mindset. You are not afraid to roll up your sleeves and write code, review pull requests, and lead by example.

Nice To Haves

Experience in the media or publishing industry is a strong plus.
Experience with Customer Data Platforms (CDPs) like Segment, Tealium, Census, or Blueconic
Familiarity with building and exposing data via RESTful APIs.
Experience with data orchestration tools like Airflow or Dagster.
Knowledge of data privacy and compliance regulations (e.g., GDPR, CCPA)

Responsibilities

Lead the design, development, and evolution of our enterprise data architecture on Snowflake and data models framework in dbt, ensuring they meet current and future business needs for scalability, performance, and cost-effectiveness
Design the evolution of the semantic layer, creating a centralized, reliable, and well-governed source of truth for all key business metrics and entities (e.g., user, content, subscription).
Establish and evangelize company-wide standards for data definitions, metrics, and KPIs. Create the frameworks and governance models that ensure consistency and trust in data across all teams
Oversee and contribute to the end-to-end data modeling lifecycle, from conceptual and logical design to physical implementation. Design data models for complex domains like audience segmentation, content performance, and revenue attribution.
Build and lead a Data Center of Excellence, defining and documenting best practices, design patterns, and standards for data engineering, data quality, and data governance.
Design a comprehensive data quality and observability framework using tools like Monte Carlo and dbt tests, ensuring proactive monitoring, alerting, and root cause analysis for all critical analytics data pipelines
Provide technical data leadership on projects involving instrumentation for new product launches, customer data platform, experimentation, analytics, and data services APIs.
Act as a key technical mentor for analytics engineers and analysts on the team. Collaborate with and influence cross-functional stakeholders to ensure data strategies are aligned with business objectives and that our platforms can support advanced measurement and segmentation.