Data Engineering Lead

In this role you will build and lead the data engineering capability for 5 Streaming, owning pipelines, models and data quality to create a single view of content and audience performance. You will design and operate pipelines powering streaming reporting and analytics, establishing a joined view across behavioral, advertising, marketing and registration data. You will codify metrics, governance and experimentation, and guide data strategy with Skydance and privacy teams. You’ll enable churn, targeting and personalization models and drive AI/automation opportunities in the data stack. This role combines technical ownership with cross-functional leadership in a fast-paced media environment.

• Own the design, build and operation of data pipelines and data models powering streaming reporting, dashboards and analysis
• Create a unified view of content and audience performance by standardizing identity and content spine across data sources
• Define and reconcile core streaming metrics and business logic across systems
• Oversee analytics implementation and tagging governance across streaming platforms
• Develop technical specifications, naming standards and defect prioritisation with product, tech and QA teams
• Implement data quality monitoring, alerts and scorecards with clear ownership and escalation
• Establish an experimentation capability with templated test setups and analysis patterns for non-technical teams
• Build in-house data modelling for churn, reactivation, targeting, segmentation and personalization
• Own the data roadmap including AI/automation opportunities to improve accuracy, timeliness and cost of the data stack
• Collaborate with Skydance data teams as the technical data counterpart and provide direction to analytics
• Govern streaming datasets in collaboration with privacy and information security to embed compliance in workflows

• Senior level data engineering experience with lead ownership of a data platform
• Expert SQL and Python with production ETL/ELT pipeline experience at scale
• Deep experience with a modern cloud data warehouse and orchestration tools
• Strong knowledge of digital/product analytics platforms and event tracking across web, mobile, and connected TV
• Experience joining behavioural, advertising and CRM data and resolving cross-source identity and metric definitions
• Proven track record in data quality governance and trusted metrics where none existed
• Practical knowledge of A/B testing and enabling experimentation for non-technical teams

• cross-functional collaboration
• stakeholder communication
• problem solving
• ETL/ELT pipeline design and operation
• cloud data warehouse (modern)
• data governance and quality monitoring