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Salary: USD 179,000 - 253,500 / annual
Scribd, Inc. (which includes Scribd, Slideshare, Everand, and Fable) is seeking a Principal/Lead Analytics Engineer to scale data infrastructure for an AI-native organization. The Data & Analytics team is building the technical foundations that enable intelligence to scale across the company by transforming fragmented data, inconsistent definitions, and dispersed analytical knowledge into trusted, reusable, production-quality data foundations.
In this role, you will operate as a senior individual contributor, shaping technical foundations, modeling standards, and development practices for the Analytics Engineering team. You will provide technical leadership by connecting Analytics Engineering investments to company priorities, communicating tradeoffs to senior leaders, and contributing to decisions about data modeling, architecture, governance, quality, tooling, and developer experience. Your impact comes through credible technical judgment paired with proximity to the work.
Key responsibilities include:
- Building canonical datasets, shared metrics, and semantic layers that enable self-serve analytics at scale
- Designing and implementing data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems
- Developing AI agents and analytical tools that bring reliable intelligence into team workflows and decisions
- Leading cross-functional data initiatives from strategy through production adoption and measurable business impact
- Raising the quality of systems, decisions, and execution across teams through technical leadership
- Balancing immediate stakeholder needs with long-term investments in reusable data products and platform health
- Communicating early and often with technical teams, business stakeholders, and senior executives
The role emphasizes pragmatism, transparency, and a curiosity about AI technologies—applying them where they create clear, measurable value to strengthen human judgment and creativity rather than replace it.
Scribd, Inc. operates on a Scribd Flex model with occasional in-person attendance required for all employees regardless of location. The company prioritizes a culture of GRIT (Goals, Results, Innovation, Team) and values employees who are real, bold, and empowered to take action.
REQUIREMENTS:
- 10+ years of experience in analytics engineering, data engineering, business intelligence engineering, or related discipline
- Depth in building governed, canonical data models and semantic layers with authoritative, discoverable definitions
- Experience designing data quality, observability, documentation, governance, access control, privacy, lineage, and evaluation systems for reliable, explainable, trustworthy AI and data products at scale
- Experience designing and building canonical data models and semantic layers supporting self-serve analytics for Finance, Legal, Operations, Marketing, Research, and other business teams
- 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 with 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
NICE TO HAVES:
- Advanced Python experience
- Experience leading data cleanup efforts and implementing role-based access controls and data retention policies
- Experience leading on-call rotations, coordinating incident response, resolving production issues, and driving follow-up improvements
