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

This role plays a critical, hands-on part in evolving and strengthening the organisation's modern data ecosystem. It is a platform-focused position for a senior technologist who thrives at scale, designing and implementing robust, performant, and governed data architecture that powers analytics, reporting, and decision-making across the organisation. The role combines deep technical expertise with practical leadership, helping define architecture and modelling standards, mentoring engineers and analysts, and partnering closely with platform and analytics teams to deliver reliable, scalable data systems.

• Design and implement scalable data architecture patterns on Snowflake to support high-volume event and analytics workloads, with a strong focus on performance, security, and cost efficiency through query optimisation, warehouse sizing, storage management, and governance best practices.
• Lead the technical design and implementation of complex data systems and platform enhancements, establishing and maintaining architecture and data modelling standards that promote consistency, scalability, and reliability across Snowflake and dbt workflows.
• Define and implement secure, scalable data access patterns, leveraging role-based access control and managed access schemas to ensure data is governed, auditable, and accessible to the right audiences.
• Design and operate data quality and observability frameworks, using dbt tests and monitoring tools to track pipeline health, latency, and freshness, and to continuously improve platform reliability and operational visibility.
• Partner closely with platform engineering and analytics teams to improve system reliability, scalability, and operational efficiency, contributing to platform architecture planning and technical roadmaps.
• Translate complex analytics and business requirements into clean, well-governed semantic data models that enable trusted self-service analytics and consistent metrics across BI tools.
• Define and implement data lifecycle and retention strategies that balance performance, cost efficiency, compliance, and data availability across the analytics platform.
• Act as a technical mentor and thought leader, helping grow the skills of engineers and analysts and raising the overall bar for data architecture and engineering practices.

• 5–8 years of experience in data engineering, data architecture, or a related field, with demonstrated ownership of production data systems or platform components.
• Deep expertise in cloud data warehousing, with hands-on experience in Snowflake, including performance tuning, security design, cost optimisation, and large-scale data modelling.
• Strong experience designing and maintaining dbt-based transformation workflows, including testing, performance optimisation, and deployment best practices.
• Experience working with event or clickstream data, ideally using Snowplow or comparable technologies, and a strong understanding of instrumentation and processing challenges at scale.
• Proven ability to design and implement semantic layers and analytics-ready data models that serve as a trusted source of truth for BI tools such as Looker, Tableau, or Domo.
• Excellent communication and stakeholder engagement skills, with the ability to explain complex technical concepts to non-technical audiences, influence architectural decisions, and build alignment across teams.

• Experience with Customer Data Platforms (CDPs).
• Experience with data orchestration tools such as Airflow or Dagster.
• Familiarity with data privacy and compliance requirements (e.g., GDPR, CCPA).
• Experience working in the media, publishing, or digital content industry.

• Actual salaries will vary based on a variety of job-related factors, including but not limited to geographic location, external market data, internal equity, skill set, experience, training, education, and/or performance.
• Base pay is just one component of the total compensation package; other rewards may include annual bonuses, short- and long-term incentives, and programme-specific awards.

• Health insurance coverage
• Employee wellness program
• Life and disability insurance
• Retirement savings plan
• Paid holidays, sick time, and vacation