Lead Analytics Engineer, AI Native Self Service Analytics

Scribd, Inc. is on a mission to advance human understanding. Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise.

Culture at Scribd, Inc.

We support a culture where our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer.

We believe the best work happens when individual flexibility is balanced with meaningful community connection. Scribd Flex empowers employees to choose the workstyle and location that support their best performance, while committing to intentional in-person moments that strengthen collaboration and culture. Occasional in-person attendance is required for all Scribd, Inc. employees, regardless of location.

So what are we looking for in new team members? At Scribd, Inc., we hire for “GRIT.” Traditionally defined as the intersection of passion and perseverance toward long-term goals, GRIT reflects the mindset we expect from every employee. For us, it also serves as a practical framework for how we work: setting and achieving Goals, delivering Results within your role, contributing Innovative ideas and solutions, and strengthening the broader Team through collaboration and attitude.

This posting reflects an approved, open position within the organization.

The Team

Data & Analytics is building the DNA of an AI native Scribd, Inc. Bringing together Analytics Engineering, Data Science, and Data Analytics, D&A partners across product, technology, content, and the business to scale intelligence, advance understanding, shape strategy, and turn insight into lasting growth across our four brand portfolio.

Making this ambition real at scale starts with Analytics Engineering. The team transforms fragmented data, inconsistent definitions, and dispersed analytical knowledge into trusted, reusable, production quality data foundations and products that enable intelligence to scale across the company.

In partnership with Engineering, Analytics Engineers ensure critical data is captured, centralized, documented, secured, and governed. The team builds canonical datasets, shared metrics, and semantic layers, together with the quality, observability, lineage, and evaluation systems that make these assets trustworthy. On top of this foundation, Analytics Engineers develop AI agents and analytical tools that bring reliable intelligence directly into the decisions and workflows of teams across the company.

The Role

We’re hiring for a Principal/Lead Analytics Engineer to scale data for an AI native Scribd, Inc. In this role, you will shape the technical foundations, modeling standards, and development practices that allow Analytics Engineering to move faster with greater confidence. You will operate as a senior individual contributor, deeply connected to the work, trusted for your judgment, and able to raise the quality of systems, decisions, and execution across teams.

Your impact will come through technical leadership. Your strong strategic judgment is paired with enough proximity to the work to guide technical decisions credibly. You will connect Analytics Engineering investments to company priorities, communicate tradeoffs clearly to senior leaders, and contribute thoughtfully to decisions about data modeling, architecture, governance, quality, tooling, and developer experience.

Your pragmatic approach keeps the organization moving forward. Rather than waiting for an ideal end state, you will think in sequences and ask, “What is the right next version?” Communication happens early and often because transparency, thoughtful feedback, and visible decision making build trust and help teams move with confidence.

The transformation happening through AI is an opportunity to expand what talented teams can accomplish. Agentic coding, AI assisted development and analysis, and automated workflows can increase human judgment, creativity, and impact rather than replace them. You approach these technologies with curiosity and pragmatism, applying them where they create clear and measurable value.

Above all, this role is about strengthening the discipline of Analytics Engineering. Success is reflected in data systems that are more reliable, understandable, scalable, and useful, and in teams that become more capable because of your technical leadership.

The Essentials

10/8+ years of experience in analytics engineering, data engineering, business intelligence engineering or a related discipline

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

Experience designing and building canonical data models and semantic layers that support self-serve analytics at scale for Finance, Legal, Operations, Marketing, Research, and other business teams.

Advanced SQL skills and 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

The 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 leading on call rotations, coordinating incident response, resolving production issues, and driving follow up improvements that strengthen system reliability

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At Scribd, Inc., your base pay is one part of your total compensation package and is determined within a range. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. San Francisco is our highest geographic market in the United States.

In the state of California, the reasonably expected salary range is between $179,000 [minimum salary in our lowest geographic market within California] to $253,500 [maximum salary in our highest geographic market within California].

In the United States, outside of California, the reasonably expected salary range is between $149,000 [minimum salary in our lowest US geographic market outside of California] to $240,500 [maximum salary in our highest US geographic market outside of California].

In Canada, the reasonably expected salary range is between $178,000 CAD[minimum salary in our lowest geographic market] to $227,000 CAD[maximum salary in our highest geographic market].

We carefully consider a wide range of factors when determining compensation, including but not limited to experience; job-related skill sets; relevant education or training; and other business and organizational needs. The salary range listed is for the level at which this job has been scoped. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for a competitive equity ownership, and a comprehensive and generous benefits package.

Working at Scribd, Inc.

• Are you currently based in a location where Scribd, Inc. can employ you?
• Employees must have their primary residence in or near one of the following cities. This includes surrounding met