Our four products — Scribd®, Slideshare®, Everand™, and Fable — help billions of people across the globe move beyond access and into insight, application, and expertise. 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. 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.

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. 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.

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. 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. ~ 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.

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. Our pay ranges are based on the local cost of labor benchmarks for each specific role, level, and geographic location. 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 Canadian market]. relevant education or training; In the event that you are considered for a different level, a higher or lower pay range would apply.

This position is also eligible for a competitive equity ownership, and a comprehensive and generous advantages package.

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 Wellness and home office stipends Enterprise access to leading AI tools 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. #

📌 Senior Manager, Data Engineering (Quebec)
🏢 Scribd
📍 Quebec