Staff Data Engineer

Position Overview

At Scribd Inc., our mission is to spark human curiosity by democratizing the exchange of ideas through our products—Everand, Scribd, Slideshare, and Fable. As a Staff Data Engineer on the Data Platform team, you will design and implement advanced data models and pipelines using modern lakehouse technologies, shaping a world-class data ecosystem for millions of users.

Key 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 to enhance data quality, governance, and performance.
• Mentor engineers by fostering a culture of ownership, operational excellence, and continuous learning.
• Shape the long-term technical vision and roadmap for Scribd’s data platform.

Required Qualifications

• 8+ years of experience in data engineering, with expertise in data architecture, modeling, and distributed 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 for multiple downstream use cases.
• Experience implementing modern data orchestration patterns for batch and streaming workloads.
• Demonstrated ability to lead technical initiatives, set standards, and influence cross-team decisions.
• Proven comfort in owning systems end-to-end, including monitoring, reliability, and cost management.
• Excellent communication skills to translate technical trade-offs for diverse audiences.

Preferred Qualifications

• 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 tools like Datadog.
• Collaborative experience with Analytics teams to translate business requirements into data solutions.

Benefits & Perks

• Compensation: Base pay ranges vary by location: In California, between $167,000 and $260,500; Outside California in the US, between $137,500 and $247,500; in Canada, between $175,000 CAD and $231,500 CAD. Competitive equity ownership is also available.
• Healthcare Insurance: 100% paid Medical, Dental, and Vision coverage for employees.
• 12 weeks paid parental leave.
• Short-term and long-term disability plans.
• 401k/RSP matching.
• Onboarding stipend for home office peripherals and accessories.
• Learning & Development allowance and programs.
• Quarterly stipend for wellness, WiFi, etc.
• Mental Health support and resources.
• Free subscription to the Scribd Inc. suite of products.
• Referral bonuses, book benefits, sabbaticals, and company-wide events.
• Team engagement budgets, vacation & personal days, paid holidays (+ winter break), and flexible sick time.
• Volunteer day and employee resource groups supporting an inclusive workplace.
• Access to AI Tools: Free access to best-in-class AI tools to boost productivity and spark innovation.