26 days ago
Base Salary
$149k - $265k/yr
Responsibilities
- Shape technical foundations, modeling standards, and development practices for Analytics Engineering.
- Design and build governed canonical data models and semantic layers that support scalable self-service analytics.
- Create data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems.
- Lead cross-functional data initiatives from strategy through production adoption and measurable business impact.
- Guide decisions involving data architecture, governance, tooling, developer experience, technical debt, and platform health.
- Communicate tradeoffs and technical decisions to engineering teams, business stakeholders, and senior executives.
- Develop AI agents and analytical tools that deliver reliable intelligence into company workflows.
- Support data cleanup, role-based access controls, data retention policies, on-call rotations, incident response, and follow-up reliability improvements.
Requirements
- 10+ years of experience in analytics engineering, data engineering, business intelligence engineering, or a related discipline.
- Deep experience building governed canonical data models and semantic layers with authoritative, discoverable business definitions.
- Experience designing data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems.
- Experience supporting self-service analytics at scale for Finance, Legal, Operations, Marketing, Research, and other business teams.
- Advanced SQL skills and production experience with a 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 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.
- Advanced Python is preferred.
- Experience with data cleanup, role-based access controls, data retention policies, on-call rotations, incident response, and production reliability improvements is preferred.
Benefits
- Scribd Flex flexible work model with occasional in-person attendance required, and primary residence near specified cities in the United States, Canada, or Mexico.
- Comprehensive health, dental, vision, mental health, and disability coverage.
- Paid time off including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals.
- Paid parental leave and family support benefits.
- Retirement matching, employee equity, wellness and home office stipends.
- Learning and development programs, professional growth opportunities, complimentary access to Scribd products, and enterprise access to leading AI tools.
