Director of Data Engineering

About the role

The Director of Data Engineering at Philo is responsible for owning and driving the vision, strategy, and execution of the Data Engineering and Analytics Engineering teams. This role sets the long-term direction for the entire data platform, leads and grows a team of data and analytics engineers, and rolls up her sleeves to architect and build alongside them.

Responsibilities

• Own the vision and technical strategy for data engineering and analytics engineering at Philo, setting the direction for how data is ingested, modeled, and delivered across the organization
• Own the team’s roadmap, balancing strategic long-term investments with near-term stakeholder needs
• Lead and grow the Data Engineering team, including hiring, career development, performance management, and supporting the team in generally thriving
• Lead the design and implementation of Philo's data platform architecture, including setting technical standards and best practices for data engineering and analytics engineering work
• Collaborate with cross-functional teams to understand data platform needs and translate business requirements into technical solutions
• Build and maintain stakeholder trust in data and reporting — ensuring that business teams have reliable, well-documented, and well-understood data products
• Design scalable data pipelines and infrastructure; drive technical decisions with a focus on long-term sustainability
• Implement data governance, security, and quality control processes as needed
• Deliver on the alchemy of transforming raw, messy application data into trusted business insight through scalable dimensional modeling and a metric layer that faithfully reflects product and customer behavior.

Key Qualifications

• 10+ years of professional experience spanning data engineering and analytics engineering, ideally with a few years working on high-volume data platforms
• 4+ years of experience managing and leading data teams, with demonstrated experience owning both data engineering and analytics engineering functions at a prior organization
• Deep expertise in modern data stack technologies, particularly AWS data services, Snowflake, dbt, Airflow, Airbyte, Python, and SQL
• Deep expertise in analytics engineering, including dbt model design, dimensional modeling, and delivering trusted, business-facing data products
• Strong people management skills with experience providing coaching, performance feedback, and career development guidance to direct reports.
• Track record of improving stakeholder trust in reporting and data quality across an organization
• Strong track record of designing and implementing data platforms
• Excellent communication skills with technical and non-technical stakeholders, simplifying complex data concepts for various business audiences

Ideal Qualifications

• Experience in media/streaming industry with understanding of video delivery analytics and metrics
• Demonstrated experience driving organizational alignment around data definitions, metrics, and a single source of truth
• Experience with data governance and compliance requirements
• Background in implementing data quality frameworks