Senior Manager, Data Engineering

Culture at Scribd, Inc.

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.

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.

Scribd’s Data Platform team builds the data pipelines, storage layers, and developer tooling that power analytics, experimentation, ML, and product features across Scribd, Everand, and Slideshare. We’re in the middle of a multi‑year investment to modernize our data architecture, with a strong focus on building well‑modeled, governed, and trusted data that teams across the company can rely on.

At Scribd, data drives everything—from product decisions and experimentation to understanding subscriber behavior and key business metrics. This role sits at the center of that effort and will play a critical part in shaping how data is structured, governed, and leveraged across the organization — including enabling trusted, well‑governed data foundations for analytics and emerging AI‑driven experiences.

As a Senior Manager, Data Engineering, you’ll lead a team responsible for building trusted, reusable data products that power analytics, experimentation, AI, and decision‑making across Scribd.

This role combines technical leadership, engineering management, and execution leadership. You’ll remain close to the technical work by guiding architecture, reviewing designs, and contributing hands‑on where your expertise creates the greatest leverage. You’ll establish engineering standards, guide architecture and design decisions, partner closely with stakeholders across the business, and help build a high‑performing team that delivers trusted, reusable data products.

You’ll work closely with our Principal Data Engineer, who leads the technical direction of our Platform Engineering function, while partnering with the Director of Data Platform on long‑term strategy, organizational planning, and cross‑functional priorities.

• Provide technical, delivery, and people leadership for the Data Engineering team responsible for building data pipelines, trusted Medallion datasets, and reusable data products.
• Establish engineering standards for data modeling, pipeline design, reliability, observability, and operational excellence.
• Drive architecture discussions and design reviews, helping engineers make thoughtful technical decisions.
• Lead execution across multiple concurrent initiatives by bringing clarity to ambiguous problems, partnering with technical leads to prioritize work, manage dependencies, and deliver predictable outcomes.
• Coach, mentor, and grow a team of Data Engineers, fostering a culture of ownership, collaboration, and continuous improvement.
• Partner closely with Product, Analytics, Data Science, and Engineering teams to translate business needs into scalable data solutions.
• Build strong cross‑functional relationships while balancing short‑term delivery with long‑term investments in reusable data foundations.
• Collaborate closely with Data Platform…