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Scribd, Inc.

Senior Manager, Data Engineering

Posted Yesterday
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In-Office
Los Angeles, CA, USA
155K-265K Annually
Senior level
In-Office
Los Angeles, CA, USA
155K-265K Annually
Senior level
Lead and grow a Data Engineering team to build production data pipelines, medallion datasets, and reusable data products. Drive architecture, engineering standards, design reviews, and cross-functional delivery. Partner with Product, Analytics, Data Science, and Platform to enable governed, reliable data foundations for analytics and AI. Mentor engineers and manage multiple concurrent initiatives to deliver predictable outcomes.
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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.

About the Team

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.

About the Role

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.

What You’ll Do
  • 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 Engineering to influence and evolve the platform capabilities that enable scalable data development across Scribd.

You Have
  • 10+ years of experience in Data Engineering, Data Platform, or related data roles.

  • 3+ years leading engineering teams, including coaching, performance management, and organizational development.

  • Deep expertise building scalable data platforms and production-grade data pipelines.

  • Strong experience with dimensional modeling, data architecture, and designing reusable analytical datasets.

  • Advanced SQL skills and strong experience with Python, Scala, or similar programming languages.

  • Experience with distributed data processing frameworks such as Spark.

  • Experience working with modern cloud data platforms such as Databricks, Delta Lake, Snowflake, or BigQuery.

  • Proven experience driving complex cross-functional initiatives from concept through production.

  • Experience leading technical architecture discussions and engineering design reviews.

  • Strong technical judgment and the ability to balance pragmatic delivery with long-term architectural thinking.

  • Excellent communication skills and experience influencing technical decisions across multiple engineering teams.

Preferred Skills
  • Experience with Databricks and Delta Lake.

  • Experience building modern data platforms and Medallion-style architectures.

  • Experience with data governance, lineage, or metadata management.

  • Experience supporting AI, ML, or analytics workloads through high-quality data foundations.

  • Experience working in subscription, payments, or consumer product domains

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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 $187,000 [minimum salary in our lowest geographic market within California] to $265,000 [maximum salary in our highest geographic market within California].

 

In the United States, outside of California, the reasonably expected salary range is between $154,500 [minimum salary in our lowest US geographic market outside of California] to $252,000 [maximum salary in our highest US geographic market outside of California].

 

In Canada, the reasonably expected salary range is between $165,000 CAD[minimum salary in our lowest geographic market] to $248,000 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 metro areas or locations within a typical commuting distance:


United States:

Atlanta | Austin | Boston | Dallas | Denver | Chicago | Houston | Jacksonville | Los Angeles | Miami | New York City | Phoenix | Portland | Sacramento | Salt Lake City | San Diego | San Francisco | Seattle | Washington D.C.

Canada:

Ottawa | Toronto | Vancouver

Mexico:

Mexico City

Benefits at Scribd, Inc.

  • 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

Get to Know Scribd, Inc.
About Scribd, Inc.
Life at Scribd, Inc.

We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing [email protected] about the need for adjustments at any point in the interview process.

If you apply for a job with Scribd or otherwise engage with us in connection with employment (including as an employee, contractor, or other personnel), the personal information we process in that context is subject to our Employee and Applicant Privacy Policy, which is available here.

Scribd, Inc. is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law. We encourage people of all backgrounds to apply, and believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.

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