Senior Manager, Data Engineering

Scribd, Inc.

Miami (FL)

On-site

USD 154,500 - 252,000

Full time

14 days+

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Benefits offered by this job

Flex work model
Health coverage
Paid time off
Parental leave
Equity

Job summary

Scribd, Inc. is seeking a Senior Manager of Data Engineering to lead a team delivering trusted data products and reusable data solutions that power analytics, experimentation, AI, and decision-making. You’ll guide architecture, review designs, and contribute hands-on where needed to maximize leverage.

You’ll mentor engineers, establish standards, and partner with Product, Analytics, Data Science, and other teams to ensure scalable, well-governed data foundations across Scribd’s platforms.

Qualifications

  • 10+ years of experience in Data Engineering, Data Platform, or related data roles.
  • 3+ years leading engineering teams, including coaching and performance management.
  • Strong track record building scalable data platforms and production-grade data pipelines.

Responsibilities

  • Provide technical, delivery, and people leadership for the Data Engineering team.
  • Establish engineering standards for data modeling, pipelines, reliability, and observability.
  • Drive architecture discussions and design reviews for scalable data solutions.
  • Lead multiple initiatives, clarify ambiguous problems, and deliver in a timely manner.
  • Coach and grow a team of Data Engineers with a culture of ownership.
  • Partner with Product, Analytics, Data Science, and Engineering teams to translate business needs into data solutions.
  • Build cross-functional relationships balancing delivery with long-term data foundations.
  • Collaborate with Data Platform Engineering to evolve platform capabilities.

Skills

Data Engineering
Team Leadership
Data Modeling
SQL
Python/Scala
Spark
Databricks
Cloud Platforms
Cross-functional Collaboration
Data Governance

Tools

Databricks
Delta Lake
Snowflake
BigQuery

Job description

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.

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.
Working at Scribd, Inc.

In the state of California, the reasonably expected salary range is between $187,000 and $265,000. In the United States, outside of California, the range is between $154,500 and $252,000. In Canada, the range is between $165,000 CAD and $248,000 CAD. This position is eligible for competitive equity ownership and a comprehensive and generous benefits package.

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

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 accommodations@scribd.com 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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