Senior Manager, Data Engineering

Scribd, Inc.; Austin (CO); Hybrid; USD 154,500 - 252,000; Full time

Benefits offered by this job

Flexible work model

Comprehensive health coverage

Generous paid time off

Paid parental leave

Job summary

Scribd, Inc. is seeking a Senior Manager, Data Engineering to lead a team responsible for building trusted and reusable data products that support analytics and experimentation. The role demands technical leadership combined with engineering management.

Your expertise in data architecture and cloud platforms will contribute to enhancing Scribd's data analytics capabilities. The ideal candidate will have a strong background in data engineering and team leadership.

Qualifications

• 10+ years of experience in Data Engineering or Data Platform roles.
• Strong experience with dimensional modeling and data architecture.
• Experience leading engineering teams and managing performance.

Responsibilities

• Lead the Data Engineering team to build trusted data products.
• Establish engineering standards for data modeling and pipeline design.
• Drive architecture discussions and help engineers with technical decisions.

Skills

Data Engineering

Leadership

SQL

Python

Data Architecture

Spark

Education

10+ years in Data Engineering

Tools

Databricks

Delta Lake

Snowflake

BigQuery

Job description

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.

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 and partner 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.

Compensation

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]. This position is also eligible for competitive equity ownership and a comprehensive and generous benefits package.

Benefits

• 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

Location

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

Equal Opportunity

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. If you require any reasonable accommodation during the interview process, please email [e-mail].