Senior Data Engineering Manager

Zoom•Seattle, WA

7d•Hybrid

About The Position

The Senior Data Engineering Manager will lead a globally distributed, cross-functional team supporting Zoom’s Online business. The role sets technical and architectural direction for the data pipelines, models, infrastructure, and analytics used across billing, checkout, growth, and revenue. It partners with Data Science, Finance, Product, and other business and engineering groups to deliver reliable, governed data assets and business insights at scale. This is a hybrid position requiring on-site presence three days per week at Zoom’s Seattle, Washington, or San Jose, California office; remote arrangements are not available.

Requirements

10+ years of experience in data engineering, including 3+ years leading and managing engineering teams.
Proven track record building and scaling production data pipelines and data platforms.
Hands-on experience with Snowflake, Databricks, Spark, Airflow, and dbt.
Strong foundation in data modeling, ETL/ELT architecture, and data governance and access-control practices.
Experience collaborating with Finance, Business, and Data Science stakeholders on revenue, billing, or growth analytics.
Demonstrated ability to hire, develop, and retain high-performing engineering talent.
Excellent communication skills across technical and executive audiences.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent experience.

Nice To Haves

Familiarity with BI and visualization tools such as Tableau, Hex, or Looker.

Responsibilities

Lead and grow a cross-functional team of data engineers, ML engineers, and data visualization engineers.
Own the roadmap and delivery of scalable data pipelines, data models, and infrastructure supporting Online business analytics, including funnel, billing, checkout, and revenue.
Partner with Data Science, Finance, and Product stakeholders to translate business requirements into reliable, well-governed data assets.
Drive data quality, classification and access-control compliance, and platform reliability across Snowflake, Databricks, and Zoom’s big-data platform ecosystem.
Define technical direction for data architecture, pipeline design, and tooling selection, including evaluating and adopting new BI and analytics platforms.
Manage team performance, hiring, mentorship, and career development to build and retain high-performing engineering talent.
Collaborate with engineering leadership on headcount planning, prioritization, and capacity allocation.