Director of Analytics Engineering

Scribd • San Francisco, CA

9d • Hybrid

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, establishing an operating model that balances structure with flexibility, and fostering a culture that supports both individual and company success. The director will create technical foundations and standards of excellence, and their leadership philosophy is grounded in service, providing clarity, context, and removing obstacles for their team. They will strengthen team dynamics, recognize great work, create career pathways, and help individuals navigate 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 to build trust. Strong strategic judgment, combined with proximity to the work, will guide technical decisions credibly. The role will connect analytics engineering investments to company priorities, communicate tradeoffs clearly to senior leaders, and contribute to decisions about data modeling, architecture, governance, quality, tooling, and developer experience. The transformation through AI is seen as an opportunity to expand team capabilities through agentic coding, AI-assisted development, and automated workflows. Ultimately, leadership is about building people and strengthening their shared discipline, resulting in a team that grows more capable, confident, connected, and effective.

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.
• 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.
• Build durable teams by distributing ownership, developing leaders, and creating 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.
• Build people and strengthen the discipline they share.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed