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Staff Data Engineer
Staff Data EngineerScribd, Inc. • Vancouver, Metro Vancouver Regional District, CA
Staff Data Engineer

Staff Data Engineer

Scribd, Inc. • Vancouver, Metro Vancouver Regional District, CA
Il y a 1 jour
Type de contrat
  • Temps plein
Description de poste

About The Company

At Scribd (pronounced “scribbed”), our mission is to spark human curiosity. Join our team as 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 our employees can be real and be bold; where we debate and commit as we embrace plot twists; and where every employee is empowered to take action as we prioritize the customer. Scribd Flex offers flexible work options; employees – in partnership with their manager – can choose the daily work-style that best suits individual needs. A key tenet of Scribd Flex is prioritizing intentional in-person moments to build collaboration, culture, and connection. For this reason, occasional in-person attendance is required for all Scribd employees, regardless of location.

We hire for “GRIT”. The acronym outlines the standards we hold ourselves to : Goals, Results, Innovation, and Team collaboration.

What You’ll Do

As a Staff Data Engineer, you’ll be both a hands-on technical expert and a strategic leader. You’ll drive the design of core data models and pipelines in our Databricks / Delta Lake lakehouse, setting standards for quality, reliability, and scalability across the platform. You’ll own end-to-end solutions from architecture through operations and optimization, guide the long-term direction of Scribd’s data ecosystem, collaborate across teams to translate complex business problems into robust data solutions, and mentor engineers to help them grow. You’ll help the team evolve toward a fully governed lakehouse with fine-grained access controls and consistent lineage.

You Will

  • 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.
  • At Scribd, base pay is part of total compensation and varies by role, level, and location. Salary ranges reflect local benchmarks. In California : $167,000 to $260,500. In the United States outside California : $137,500 to $247,500. In Canada : C$175,000 to C$231,500. The final offer considers experience, skills, education, and business needs. This position may be eligible for equity and a comprehensive benefits package.

    Working at Scribd

    Are you based in a location where Scribd can employ you? Primarily, you must reside in or near listed cities within the United States, Canada, or Mexico, as applicable to the role.

    Benefits, Perks, And Wellbeing At Scribd

  • Benefits / perks may vary by employment type and location.
  • 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 wellness, WiFi, and related stipends
  • Mental health resources
  • Free Scribd product subscriptions
  • Referral bonuses
  • Book benefit, sabbaticals, and company-wide events
  • Team engagement budgets and flexible time off
  • AI tools access to boost productivity
  • For more about life at Scribd, visit www.linkedin.com / company / scribd / life. We are committed to equal employment opportunity and welcome applicants from diverse backgrounds. If you need adjustments during the interview process, contact accommodations@scribd.com.

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