Senior Manager of Data Engineering

Join Scribd, Inc. as a Senior Manager of Data Engineering. In this role, you will lead a team responsible for building trusted, reusable data products that power analytics, experimentation, AI, and decision-making across the organization. You will establish engineering standards, guide architecture and design decisions, and partner closely with stakeholders across the business. This position offers a competitive salary and a comprehensive benefits package, including healthcare coverage, paid parental leave, and a 401k matching plan.

• Lead a team responsible for building trusted, reusable data products that power analytics, experimentation, AI, and decision-making across Scribd, Inc.
• Establish engineering standards, guide architecture and design decisions, partner closely with stakeholders across the business, and help build a high-performing team.
• Drive architecture discussions and design reviews, helping engineers make thoughtful technical decisions, and lead execution across multiple concurrent initiatives.
• Experience with distributed data processing frameworks such as Spark
• Experience leading technical architecture discussions and engineering design reviews
• Excellent communication skills and experience influencing technical decisions across multiple engineering teams
• Proven experience driving complex cross-functional initiatives from concept through production
• 3+ years leading engineering teams, including coaching, performance management, and organizational development
• Advanced SQL skills and strong experience with Python, Scala, or similar programming languages
• 10+ years of experience in Data Engineering, Data Platform, or related data roles
• Experience working with modern cloud data platforms such as Databricks, Delta Lake, Snowflake, or BigQuery
• Strong technical judgment and the ability to balance pragmatic delivery with long-term architectural thinking
• Strong experience with dimensional modeling, data architecture, and designing reusable analytical datasets
• Deep expertise building scalable data platforms and production-grade data pipelines
• Experience working in subscription, payments, or consumer product domains
• Experience supporting AI, ML, or analytics workloads through high-quality data foundations
• Experience with data governance, lineage, or metadata management
• Experience building modern data platforms and Medallion-style architectures
• Experience with Databricks and Delta Lake