Director of Analytics Engineering
About The Position
Scribd, Inc. is seeking a Director of Analytics Engineering to own scaling data for an AI-native company. This role involves building, scaling, and leading a high-performing Analytics Engineering team. The focus is on establishing an operating model that provides structure without bureaucracy, fostering a culture that balances local priorities with company success, and creating technical foundations and standards of excellence. The leadership philosophy is grounded in service, aiming to provide clarity, create context, remove obstacles, and help others succeed. The role emphasizes strengthening team dynamics, recognizing great work, creating career pathways, and supporting individuals through their careers. A pragmatic approach is key, focusing on the 'right next version' rather than an ideal end state, with communication happening early and often. Strong strategic judgment is required, with the ability to connect analytics engineering investments to company priorities, communicate tradeoffs to senior leaders, and contribute to decisions on data modeling, architecture, governance, quality, tooling, and developer experience. The role also involves leveraging AI technologies like agentic coding and AI-assisted development to increase human judgment, creativity, and impact.
Requirements
- 10+ years of experience in analytics engineering, data engineering, business intelligence engineering or a related discipline.
- 5+ years leading and developing technical teams.
- Proven track record of building, scaling, and leading high performing teams, turning strong individual contributors into cohesive and highly effective teams that are valued as strategic partners.
- Depth in building governed, canonical data models and semantic layers, giving core business concepts one authoritative, discoverable definition instead of letting teams reconcile competing sources.
- Experience designing the data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems that ensure data and AI products are reliable, explainable, trustworthy, and safe to operate at scale.
- Advanced SQL skills.
- Production experience with modern data stack, including AWS, Databricks, Airbyte, Fivetran, Looker, or comparable platforms.
- Demonstrated ability to lead cross functional data initiatives from strategy through production adoption and measurable business impact.
- Strong judgment in balancing immediate stakeholder needs with long term investments in reusable data products, platform health, and technical debt reduction.
- Excellent written and verbal communication with technical teams, business stakeholders, and senior executives.
Nice To Haves
- Advanced Python
- Experience leading data cleanup efforts and implementing role based access controls and data retention policies to improve data quality, security, and governance.
- Experience designing and building canonical data models and semantic layers that support financial analysis at scale.
- Experience leading on call rotations, coordinating incident response, resolving production issues, and driving follow up improvements that strengthen system reliability.
Responsibilities
- Build, scale, and lead a high performing Analytics Engineering team, turning strong individual contributors into a cohesive and highly effective team.
- Establish an operating model that creates structure without unnecessary bureaucracy.
- Foster culture and community that balances local priorities with the broader success of the company.
- Create the technical foundations and standards of excellence that enable everyone to do their best work.
- Strengthen team dynamics, ensure great work is recognized, create meaningful career pathways, and help individuals navigate obstacles and opportunities.
- Distribute ownership, develop leaders, and create an environment where people feel trusted, supported, and accountable.
- Connect analytics engineering investments to company priorities.
- Communicate tradeoffs clearly to senior leaders.
- Contribute thoughtfully to decisions about data modeling, architecture, governance, quality, tooling, and developer experience.
- Apply AI technologies where they create clear and measurable value.
- Ensure critical data is captured, centralized, documented, secured, and governed in partnership with Engineering.
- Build canonical datasets, shared metrics, and semantic layers.
- Develop quality, observability, lineage, and evaluation systems that make data assets trustworthy.
- Develop AI agents and analytical tools that bring reliable intelligence directly into the decisions and workflows of teams across the company.
Benefits
- Scribd Flex (flexible work model)
- Comprehensive health, dental, and vision coverage
- Mental health support and disability coverage
- Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
- Paid parental leave and family support benefits
- Retirement matching and employee equity
- Learning and development programs and professional growth opportunities
- Wellness and home office stipends
- Complimentary access to the Scribd, Inc. suite of products
- Enterprise access to leading AI tools
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What This Job Offers
Job Type
Full-time
Career Level
Director
Education Level
No Education Listed
