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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 the standards for quality, reliability, and scalability across the platform. You’ll own end‑to‑end solutions, from architecture and implementation to operations and optimization, while helping guide the long‑term direction of Scribd’s data ecosystem. You’ll collaborate across teams to turn complex business problems into robust data solutions, and you’ll mentor engineers to help them grow and deliver at a higher level. You’ll help the team evolve toward a fully governed lakehouse with fine‑grained access controls and consistent lineage.
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.
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 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.
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 determined within a range.
In the state of California, the reasonably expected salary range is between $167,000 (minimum salary in our lowest geographic market within California) and $260,500 (maximum salary in our highest geographic market within California).
In the United States, outside of California, the reasonably expected salary range is between $137,500 (minimum salary in our lowest US geographic market outside of California) and $247,500 (maximum salary in our highest US geographic market outside of California).
In Canada, the reasonably expected salary range is between $175,000 CAD (minimum salary in our lowest geographic market) and $231,500 CAD (maximum salary in our highest geographic market).
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
Equal Opportunity Employment 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 accommodations@scribd.com about the need for adjustments at any point in the interview process.
Scribd, Inc. 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. Come join us in building something meaningful.
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Sprachkenntnisse
- English
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