Senior Manager, Data Engineering

About Scribd, Inc.

Scribd, Inc. is dedicated to advancing human understanding through its four main products — Scribd®, Slideshare®, Everand™, and Fable — which collectively serve billions worldwide to move beyond mere access to meaningful insights, practical application, and expertise.

Culture

Scribd fosters a culture where employees are encouraged to be authentic and bold, engage in meaningful debates, navigate changes with commitment, and prioritize customers. The company supports a balance between individual flexibility and community engagement via the Scribd Flex program, which empowers employees to select workstyles and locations that optimize performance, alongside regular in-person interactions to promote collaboration and culture. Occasional on-site attendance is mandatory for all employees, regardless of location.

Team Overview

The Data Platform team at Scribd constructs data pipelines, storage infrastructures, and tools powering analytics, experimentation, machine learning, and product features across Scribd, Everand, and Slideshare. The team is engaged in a multi-year project to modernize their data infrastructure focusing on well-designed, governed, and dependable data accessible across the company.

Role Summary

The Senior Manager, Data Engineering, leads a team building reliable, reusable data products supporting analytics, experimentation, AI, and decision-making throughout Scribd. This position involves technical and people leadership, guiding architecture and design, establishing engineering standards, aligning with stakeholders, and cultivating a high-performance team delivering dependable data products.

Key Responsibilities

• Lead and mentor the Data Engineering team in developing data pipelines, Medallion datasets, and reusable data assets.
• Define and enforce engineering principles for data modeling, pipeline architecture, reliability, observability, and operational excellence.
• Facilitate architectural discussions and design reviews, assisting engineers with technical decisions.
• Oversee and coordinate multiple projects, clarifying ambiguous challenges, prioritizing tasks with technical leads, managing dependencies, and ensuring consistent delivery.
• Coach and develop team members, encouraging ownership, collaboration, and continuous enhancement.
• Collaborate with Product, Analytics, Data Science, and Engineering units to translate business objectives into scalable data solutions.
• Maintain strong cross-functional relationships, balancing immediate deliverables with investments in reusable data infrastructure.
• Work with Data Platform Engineering teams to evolve platform capabilities enabling scalable data engineering.

Requirements

• At least 10 years of experience in Data Engineering or related data roles.
• Minimum 3 years managing engineering teams, including coaching and organizational development.
• Expertise in building scalable data platforms and production-grade pipelines.
• Proficiency in dimensional modeling, data architecture, and designing reusable analytical datasets.
• Advanced SQL capabilities and strong knowledge of Python, Scala, or related languages.
• Experience with distributed data processing frameworks like Spark.
• Familiarity with modern cloud data platforms such as Databricks, Delta Lake, Snowflake, or BigQuery.
• Proven track record in leading complex cross-functional projects from ideation to production.
• Experience leading architecture discussions and engineering design reviews.
• Sound technical judgment balancing practical delivery with long-term architectural vision.
• Excellent communication and the ability to influence technical decisions across engineering teams.

Preferred Qualifications

• Experience with Databricks and Delta Lake.
• Familiarity with modern data architectures like Medallion.
• Knowledge of data governance, lineage, or metadata management.
• Experience supporting AI, machine learning, or analytics through solid data foundations.
• Background in subscription, payments, or consumer product industries.

Compensation

Compensation for this role varies geographically and is based on factors like experience and skills. In Canada, the salary range is approximately CAD 165,000 to CAD 248,000. This includes eligibility for equity ownership and a comprehensive benefits package.

Location and Work Model

The role requires primary residence in or near Ottawa, Toronto, or Vancouver in Canada. Occasional on-site presence is mandatory despite flexible work arrangements.

Benefits

• Flexible work model (Scribd Flex)
• Comprehensive medical, dental, and vision insurance
• Mental health and disability support
• Generous paid time off including vacations, sick leave, holidays, winter break, volunteer days, and sabbaticals
• Paid parental leave and family support benefits
• Retirement matching and employee equity options
• Professional development and learning opportunities
• Wellness and home office stipends
• Free access to Scribd's product suite
• Enterprise-level access to leading AI tools

Equal Opportunity and Accessibility

Scribd is committed to creating an inclusive hiring process accessible to all applicants, providing reasonable accommodations upon request. The company values diversity and encourages applicants from all backgrounds to join in building impactful solutions.