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Staff Data Engineer

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Scribd

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Location:
United States; Canada; Mexico , San Francisco ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

137500.00 - 260500.00 USD / Year
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Job Description:

Join Scribd's Data Platform team to build data pipelines, storage layers and developer tooling that power analytics, experimentation, ML and product features. You'll help modernize the data architecture for fully governed, properly-modeled data that every team can trust and build upon, tackling complex challenges within a rich domain spanning three brands that serve over 200 million monthly visitors and 2 million paying subscribers.

Job Responsibility:

  • 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

Requirements:

  • 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

Nice to have:

  • 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
What we offer:
  • 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
  • Learning & Development programs
  • Quarterly stipend for Wellness, WiFi, etc.
  • Mental Health support & resources
  • Free subscription to the Scribd Inc. suite of products
  • Referral Bonuses
  • Book Benefit
  • Sabbaticals
  • Company-wide events
  • Team engagement budgets
  • Vacation & Personal Days
  • Paid Holidays (+ winter break)
  • Flexible Sick Time
  • Volunteer Day
  • Company-wide Employee Resource Groups and programs that foster an inclusive and diverse workplace
  • Access to AI Tools: We provide free access to best-in-class AI tools, empowering you to boost productivity, streamline workflows, and accelerate bold innovation

Additional Information:

Job Posted:
February 18, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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