Senior Manager, Data Engineering

About Scribd, Inc.

Scribd, Inc. is dedicated to advancing human understanding through its products Scribd®, Slideshare®, Everand™, and Fable, which collectively serve billions worldwide by transforming access into insight, application, and expertise.

Company Culture

We foster a culture grounded in authenticity and boldness, encouraging debate and commitment while embracing change. Employees are empowered to take decisive action with customer prioritization at the forefront. Our flexible work model balances individual work styles with meaningful community connections through intentional in-person collaboration. Occasional onsite presence is required for all employees.

Core Values - GRIT

We value GRIT, defined as the harmony of passion and perseverance towards long-term objectives. This framework guides our methods: setting clear Goals, delivering measurable Results, innovating solutions, and reinforcing team collaboration and mindset.

About The Team

The Data Platform team creates the infrastructure for data pipelines, storage, and tooling supporting analytics, experimentation, machine learning, and product features across multiple Scribd products. Currently, the team is modernizing its data architecture with an emphasis on producing governed, trustworthy data assets accessible company-wide.

Role Overview

The Senior Manager, Data Engineering leads the team responsible for creating reliable, reusable data products powering analytics, experimentation, AI, and business decisions. This role combines managerial oversight, strategic technical leadership, and hands-on contributions in architecture and design.

Key Responsibilities

• Provide leadership in technical execution, delivery, and people management of the Data Engineering team.
• Develop and uphold engineering standards around data modeling, pipeline design, reliability, observability, and operational excellence.
• Guide architecture discussions and conduct design reviews to ensure sound technical decisions.
• Manage multiple concurrent projects by clarifying ambiguous challenges, prioritizing tasks, handling dependencies, and ensuring reliable outcomes.
• Mentor and grow data engineers, promoting ownership, teamwork, and continuous improvement.
• Collaborate with Product, Analytics, Data Science, and Engineering teams to translate business needs into scalable data solutions.
• Balance immediate deliverables with long-term development of reusable data foundations.
• Work alongside Data Platform Engineering to shape platform capabilities for scalable data development.

Minimum Qualifications

• Over 10 years in Data Engineering or related data roles.
• At least 3 years of experience managing engineering teams, including performance coaching and organizational development.
• Expertise in building scalable data platforms and production-grade pipelines.
• Strong knowledge of dimensional modeling, architectures, and reusable analytical datasets.
• Advanced proficiency in SQL; skilled in Python, Scala, or equivalent languages.
• Experience with distributed data processing frameworks like Spark.
• Familiarity with cloud data platforms such as Databricks, Delta Lake, Snowflake, or BigQuery.
• Demonstrated success in leading complex, cross-functional initiatives from inception to production.
• Ability to lead technical architecture discussions and engineering design reviews.
• Strong judgment to balance quick delivery with strategic architecture planning.
• Excellent communication and influence across diverse engineering teams.

Preferred Experience

• Hands-on experience with Databricks and Delta Lake.
• Familiarity with modern Medallion architecture-style data platforms.
• Knowledge of data governance, lineage, or metadata management.
• Supporting AI, ML, or analytics workloads with solid data foundations.
• Industry experience in subscription services, payments, or consumer products.

Compensation and Benefits

Salary ranges are determined by local market cost-of-labor benchmarks and vary by region. For Canada, the expected salary band is CAD 165,000 to CAD 248,000 annually. The position includes competitive equity options and comprehensive benefits including health, dental, vision, mental health support, generous paid time off, parental leave, retirement matching, learning and development programs, wellness and home office stipends, enterprise AI tool access, and complimentary use of Scribd physical products.

Location and Employment Eligibility

Applicants must reside or be able to work near the following locations: Toronto, Ottawa, Vancouver (Canada); multiple US cities; or Mexico City, Mexico. Occasional onsite attendance is mandatory.

Equal Employment Opportunity

Scribd is committed to inclusive employment practices encouraging applicants regardless of protected characteristics, recognizing diverse perspectives as fundamental to innovation.