Senior Manager, Data Engineering

About Scribd, Inc.

Scribd, Inc. strives to advance human understanding through its products Scribd®, Slideshare®, Everand™, and Fable, reaching billions globally by transforming access into insight and expertise.

Culture

We foster an environment where authenticity and boldness thrive, encouraging debate and commitment while adapting to change. Employees are empowered with flexibility balanced by in-person collaboration moments to enhance culture and performance. All staff are expected to attend occasional on-site activities.

Core Values

We hire for GRIT—passion and perseverance toward long-term goals—manifested in setting goals, delivering results, innovating solutions, and fostering team collaboration and positive attitudes.

The Team

The Data Platform team develops data pipelines, storage, and tools powering analytics, experimentation, machine learning, and product features across Scribd’s products. They are modernizing data architecture to build consistent, governed, and reliable data accessible company-wide.

Role Overview

The Senior Manager, Data Engineering leads a team that creates trustworthy and reusable data products supporting analytics, experimentation, AI, and business decisions. This role merges technical leadership, engineering management, and project execution.

Responsibilities

• Lead and mentor the Data Engineering team delivering data pipelines, Medallion datasets, and reusable data products.
• Set engineering standards for data modeling, pipeline architecture, reliability, and operational excellence.
• Guide architectural choices and review technical designs.
• Manage multiple projects by clarifying ambiguous problems, prioritizing tasks, coordinating dependencies, and ensuring reliable delivery.
• Collaborate with Product, Analytics, Data Science, and Engineering partners to translate needs into scalable data solutions.
• Foster strong cross-functional relationships, ensuring balance between immediate deliveries and long-term data foundation investments.
• Work closely with Data Platform Engineering leaders on evolving scalable platform capabilities.

Experience and Skills Required

• Over 10 years in Data Engineering or related fields.
• At least 3 years managing engineering teams with experience in coaching and organizational growth.
• Expertise in building scalable data platforms and robust production data pipelines.
• Proficient in dimensional modeling, data architecture, and reusable analytics dataset design.
• Advanced SQL and programming skills in Python, Scala, or similar languages.
• Hands-on experience with distributed data processing frameworks like Spark.
• Familiarity with modern cloud data platforms such as Databricks, Delta Lake, Snowflake, or BigQuery.
• Track record of leading complex cross-functional initiatives from concept to delivery.
• Capability to lead technical architecture discussions and design reviews effectively.
• Strong technical judgment balancing pragmatic solutions with long-term architectural vision.
• Excellent communication skills to influence technical decisions across multiple teams.

Preferred Skills

• Experience with Databricks and Delta Lake implementations.
• Knowledge of Medallion architecture and modern data platform design.
• Familiarity with data governance, lineage, or metadata management practices.
• Experience supporting AI, machine learning, or analytic workloads through quality data foundations.
• Background working within subscription, payments, or consumer product sectors.

Compensation and Benefits

Salary ranges in Canada for this role span CAD 165,000 to CAD 248,000, with pay determined by experience, skills, education, and company needs. Additional compensation includes competitive equity ownership and comprehensive benefits.

Work Locations

Employees must be based in or near specific cities, including Vancouver, British Columbia, among other US and Canadian metro areas.

Employee Benefits

• Flexible work model (Scribd Flex)
• Health, dental, and vision insurance coverage
• Mental health and disability support
• Paid vacation, sick, holidays, volunteer time, and sabbatical options
• Parental leave and family assistance
• Retirement matching and equity participation
• Professional development and growth programs
• Wellness and home office stipends
• Free access to Scribd product offerings
• Enterprise AI tool access

Diversity and Inclusion

The company advocates equal opportunity employment regardless of any protected personal characteristic, encouraging diverse backgrounds to contribute to a vibrant, inclusive workplace.

Interview Accommodations

Applicants needing adjustments during the hiring process can request accommodations to ensure accessibility.