Senior Manager, Data Engineering

About the Team

Scribd’s Data Platform team builds the data pipelines, storage layers, and developer tooling that power analytics, experimentation, ML, and product features across Scribd, Everand, and Slideshare. We’re in the middle of a multi-year investment to modernize our data architecture, with a strong focus on building well‑modeled, governed, and trusted data that teams across the company can rely on.

As a Senior Manager, Data Engineering, you'll lead a team responsible for building trusted, reusable data products that power analytics, experimentation, AI, and decision‑making across Scribd. This role combines technical leadership, engineering management, and execution leadership. You'll remain close to the technical work by guiding architecture, reviewing designs, and contributing hands‑on where your expertise creates the greatest leverage. You'll establish engineering standards, guide architecture and design decisions, partner closely with stakeholders across the business, and help build a high‑performing team that delivers trusted, reusable data products.

You'll work closely with our Principal Data Engineer and partner with the Director of Data Platform on long‑term strategy, organizational planning, and cross‑functional priorities.

• Provide technical, delivery, and people leadership for the Data Engineering team responsible for building data pipelines, trusted Medallion datasets, and reusable data products.
• Establish engineering standards for data modeling, pipeline design, reliability, observability, and operational excellence.
• Drive architecture discussions and design reviews, helping engineers make thoughtful technical decisions.
• Lead execution across multiple concurrent initiatives by bringing clarity to ambiguous problems, partnering with technical leads to prioritize work, manage dependencies, and deliver predictable outcomes.
• Coach, mentor, and grow a team of Data Engineers, fostering a culture of ownership, collaboration, and continuous improvement.
• Partner closely with Product, Analytics, Data Science, and Engineering teams to translate business needs into scalable data solutions.
• Build strong cross‑functional relationships while balancing short‑term delivery with long‑term investments in reusable data foundations.
• Collaborate closely with Data Platform Engineering to influence and evolve the platform capabilities that enable scalable data development across Scribd.

• 10+ years of experience in Data Engineering, Data Platform, or related data roles.
• 3+ years leading engineering teams, including coaching, performance management, and organizational development.
• Deep expertise building scalable data platforms and production‑grade data pipelines.
• Strong experience with dimensional modeling, data architecture, and designing reusable analytical datasets.
• Advanced SQL skills and strong experience with Python, Scala, or similar programming languages.
• Experience with distributed data processing frameworks such as Spark.
• Experience working with modern cloud data platforms such as Databricks, Delta Lake, Snowflake, or Big Query.
• Proven experience driving complex cross‑functional initiatives from concept through production.
• Experience leading technical architecture discussions and engineering design reviews.
• Strong technical judgment and the ability to balance pragmatic delivery with long‑term architectural thinking.
• Excellent communication skills and experience influencing technical decisions across multiple engineering teams.

• Experience with Databricks and Delta Lake.
• Experience building modern data platforms and Medallion‑style architectures.
• Experience with data governance, lineage, or metadata management.
• Experience supporting AI, ML, or analytics workloads through high‑quality data foundations.
• Experience working in subscription, payments, or consumer product domains.

In the state of California, the reasonably expected salary range is between $187,000 [minimum salary in our lowest geographic market within California] to $265,000 [maximum salary in our highest geographic market within California]. In the United States, outside of California,…