Staff Data Engineer
About The Position
Scribd, Inc. is looking for a Staff Data Engineer to join their Data Platform team. This team builds and governs the analytical data models and transformation layers that power trusted metrics, experimentation, ML, and product insights across Scribd, Everand, and Slideshare. The role is a high-impact opportunity to shape Scribd’s next-generation data platform and elevate engineering practices. The Data Platform team is midway through a multi-year investment to modernize its data architecture for fully governed, properly-modeled data that every team can trust and build upon. Scribd leverages deep data insights to inform every aspect of its business, from product development and experimentation to understanding subscriber engagement and key metrics. The data engineering team tackles complex challenges within a rich domain spanning three brands that serve over 200 million monthly visitors and 2 million paying subscribers.
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 SQL expertise required — including complex joins, aggregations, window functions, CTEs, query optimization, and reasoning about data at different levels of aggregation.
- Deep experience designing dimensional and analytical data models and owning metrics across domains (analytics, ML, APIs).
- Experience designing reliable transformation workflows that maintain consistent data and business logic across batch and streaming pipelines.
- 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.
- This role requires hands-on data modeling and SQL fluency; it is not a platform-only or infrastructure-focused position.
Nice To Haves
- 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.
Responsibilities
- Design and own canonical analytical data models, defining grain, keys, and relationships that power Scribd’s enterprise metrics and reporting.
- Implement modern data lake orchestration patterns, including medallion architectures.
- Design and evolve scalable analytical data structures and transformation layers in Databricks/Delta Lake, ensuring correctness, performance, and clarity of modeled datasets.
- Define and enforce data modeling standards (grain definition, fact vs. dimension design, key strategy, naming conventions) that ensure analytical correctness and prevent metric ambiguity.
- 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.
Benefits
- 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
- Learning and development programs and professional growth opportunities
- Wellness and home office stipends
- Complimentary access to the Scribd, Inc. suite of products
- Enterprise access to leading AI tools
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
