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Salary: USD 202,500 - 268,000 / annual
Scribd is hiring a Director of Analytics Engineering to lead and scale the analytics engineering function as the company builds AI-native data foundations. You will own the strategy, team development, and technical execution of analytics engineering across Scribd's four-product portfolio (Scribd, Slideshare, Everand, Fable).
In this role, you will build and lead a high-performing analytics engineering team, transforming fragmented data and inconsistent definitions into trusted, production-quality data foundations and products. You'll establish an operating model that balances structure with pragmatism, foster a culture of ownership and accountability, and create technical standards that enable the entire organization to do their best work.
Your responsibilities include:
- Building and scaling the analytics engineering team, developing strong individual contributors into a cohesive, strategic partner organization
- Establishing governed, canonical data models and semantic layers that give core business concepts single authoritative definitions
- Designing and implementing data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems that ensure data and AI products are reliable and trustworthy at scale
- Leading cross-functional data initiatives from strategy through production adoption and measurable business impact
- Connecting analytics engineering investments to company priorities and communicating technical tradeoffs to senior leadership
- Balancing immediate stakeholder needs with long-term investments in reusable data products, platform health, and technical debt reduction
- Guiding technical decisions credibly with enough proximity to the work to understand data modeling, architecture, governance, tooling, and developer experience
- Fostering a leadership philosophy grounded in service: providing clarity, creating context, removing obstacles, and helping others succeed
Scribd operates on a Scribd Flex model with occasional in-person attendance required. The role is based in San Francisco with flexibility for employees in other approved US and Canadian metros (Atlanta, Austin, Boston, Dallas, Denver, Chicago, Houston, Jacksonville, Los Angeles, Miami, NYC, Phoenix, Portland, Sacramento, Salt Lake City, San Diego, Seattle, Washington D.C., Ottawa, Toronto, Vancouver) or Mexico City.
REQUIREMENTS:
- 10+ years of experience in analytics engineering, data engineering, business intelligence engineering, or related discipline
- 5+ years leading and developing technical teams
- Proven track record of building, scaling, and leading high-performing teams
- Depth in building governed, canonical data models and semantic layers
- Experience designing data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems
- Advanced SQL skills and production experience with modern data stack (AWS, Databricks, Airbyte, Fivetran, Looker, or comparable platforms)
- Demonstrated ability to lead cross-functional data initiatives from strategy through production adoption
- Strong judgment in balancing immediate needs with long-term investments
- Excellent written and verbal communication with technical teams, business stakeholders, and executives
NICE TO HAVES:
- Advanced Python
- Experience leading data cleanup efforts and implementing role-based access controls and data retention policies
- Experience designing canonical data models and semantic layers for financial analysis at scale
- Experience leading on-call rotations, incident response, and production issue resolution
