Job Details

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About the Company

At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. We create a world of stories and knowledge, democratize the exchange of ideas and information, and empower collective expertise through our four products: Everand, Scribd, Slideshare, and Fable. We support a culture where employees can be real and bold; where we debate, commit, and embrace plot twists; and where each person is empowered to take action as we prioritize the customer. We believe in balancing individual flexibility with community connections, offering flexible work benefits (Scribd Flex) and encouraging intentional in‑person moments to build collaboration, culture, and connection. Occasional in‑person attendance is required for all Scribd employees, regardless of location. We hire for “GRIT”—the intersection of passion and perseverance toward long‑term goals—expecting you to set goals, achieve results, contribute innovative ideas, and positively influence the broader team through collaboration and attitude.

Team Overview

The Data Platform team builds data pipelines, storage layers, and developer tooling that power analytics, experimentation, ML, and product features across Scribd, Everand, and Slideshare. We are modernizing our data architecture for fully governed, properly modeled data that every team can trust and build upon. You'll tackle complex challenges spanning three brands that serve over 200 million monthly visitors and 2 million paying subscribers, shaping Scribd's next‑generation data platform and elevating engineering practices to world‑class standards.

Role Overview

As a Staff Data Engineer, you will be both a hands‑on technical expert and a strategic leader. You will drive the design of core data models and pipelines in our Databricks/Delta Lake lakehouse, set standards for quality, reliability, and scalability, own end‑to‑end solutions, guide the long‑term direction of Scribd's data ecosystem, collaborate across teams, mentor engineers, and help evolve toward a fully governed lakehouse with fine‑grained access controls and consistent lineage.

Responsibilities

• Design and implement core data models and pipelines that power analytics, ML, and product experiences.
• Implement modern data lake orchestration patterns, including medallion architectures.
• Architect and evolve a scalable, cost‑efficient, and reliable lakehouse foundation using Databricks, Delta Lake, and Airflow.
• Define best practices and technical standards that improve data quality, governance, and performance across teams.
• Mentor engineers and foster a culture of ownership, operational excellence, and continuous learning.
• Shape the long‑term technical vision and roadmap for Scribd's data platform.

Required Skills

• 8+ years of experience in data engineering, with a strong background in data architecture, data modeling, and distributed data systems.
• Deep expertise in Databricks, Delta Lake, Spark, and modern lakehouse technologies.
• Advanced proficiency in SQL and Python or Scala, including performance optimization and large‑scale ETL design.
• Proven experience designing data models and schemas that serve multiple downstream use cases (analytics, ML, APIs).
• Experience implementing modern data orchestration patterns for big data use‑cases, including batch and streaming workloads.
• Demonstrated ability to lead technical initiatives, set standards, and influence decisions across teams.
• Comfort owning systems end‑to‑end, including monitoring, reliability, and cost management.
• Excellent communication skills with the ability to translate technical trade‑offs to both engineers and non‑technical stakeholders.

Desired Skills

• Experience with subscription, payments, or large‑scale consumer data domains.
• Familiarity with AWS data services (S3, Glue, EMR, Kinesis) and cloud cost optimization.
• Knowledge of streaming architectures (Kafka, Kinesis, or similar).
• Experience implementing data quality, governance, and observability standards at scale.
• Contributions to open‑source projects or thought leadership in the data engineering community.
• Experience operationalizing data observability through Datadog or equivalent monitoring tools.
• Experience working with Analytics teams to understand their requirements and translate to data products and data solutions.

Compensation

Base pay is one part of your total compensation package and is determined within a range. For San Francisco, the expected range is 167,000–260,500 USD. Outside California, the expected range is 137,500–247,500 USD. In Canada, the expected range is 175,000–231,500 CAD. The role also includes competitive equity ownership and a comprehensive benefits package.

Benefits, Perks, and Wellbeing

• Healthcare Insurance Coverage (Medical/Dental/Vision): 100% paid for employees
• 12 weeks paid parental leave
• Short‑term/long‑term disability plans
• 401k/RSP matching
• Onboarding stipend for home office peripherals + accessories
• Learning & Development allowance and programs
• Quarterly stipend for Wellness, WiFi, etc.
• Mental Health support & resources
• Free subscription to the Scribd suite of products
• Referral bonuses
• Book benefit
• Sabbaticals
• Company‑wide events and team engagement budgets
• Vacation & Personal Days; paid holidays (incl. winter break)
• Flexible sick time; volunteer day
• Company‑wide Employee Resource Groups fostering inclusion and diversity
• Access to AI tools and best‑in‑class AI solutions

Location Availability

To be eligible, you must have your primary residence in or near one of the following locations. Your city must be 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 Employment Opportunity

We want our interview process to be accessible to everyone. You can inform us of any reasonable adjustments we can make to better accommodate your needs by emailing ...@scribd.com. Scribd 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.