Senior Data Infrastructure Manager, YouTube Marketing

6 Months ago • 10 Years + • Data Analyst

Job Summary

Job Description

As a Senior Data Infrastructure Manager at YouTube Marketing, you'll lead a team of data engineers in building and maintaining a robust data infrastructure. This involves developing scalable data pipelines, designing insightful dashboards, and ensuring data quality and accuracy. You'll partner with various teams (marketing, data science, engineering, analytics) to drive data-driven decisions, improve campaigns, and quantify marketing impact. Responsibilities include team mentoring, architecture optimization, data model building, process automation, and collaborating on overall data strategy. You'll champion centralized data infrastructure and guide the team in adhering to best practices.

Must have:

10+ years data infrastructure experience
5+ years coding and data pipeline design
3+ years people management
SQL, dashboard building, data transformation expertise
Build and lead data engineering team
Develop and optimize data pipelines
Partner with cross-functional teams
Shape overall data strategy

Good to have:

Experience with advanced analytics (ML, statistical analytics)
Client-side media & marketing data science experience
Understanding of incrementality measurement

7 skills required

7 skills required for this role

Add these skills to join the top 1% applicants for this job

python

sql

data-science

scalability

data-driven-decisions

innovation

cross-functional

Job Details

Minimum qualifications:

Bachelor's degree or equivalent practical experience.
10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synchronous and asynchronous system integration and implementation using internal and external stacks.
3 years of experience in a people management, supervision, or team leadership role.
Experience in SQL, building dashboards, data collection/transformation, visualization/dashboards, or a scripting/programming language (e.g., Python).

Preferred qualifications:

Experience working with advanced analytics solutions involving machine learning and statistical analytics.
Experience supporting client-side media and marketing data science.
Understanding of incrementality measurement methodologies and frameworks.
Ability to operate in a fluid, constantly evolving and collaborative environment.

About the job

YouTube’s reach and engagement is exceptional. YouTube has become the expressive platform of a generation empowered to shape what matters in culture and society today. Together we are building a global destination for creativity, learning, and expression.

In this role, you will be shaping our marketing strategy through the development and maintenance of a robust data infrastructure. You will build, mentor and lead a team of talented data engineers, empowering them to build data solutions, design insightful dashboards, and establish robust data pipelines that fuel our marketing efforts. Your technical expertise and leadership will enable the marketing team to make data-driven decisions that improve campaigns and quantify the incremental impact of marketing initiatives.

YouTube/Video Global Solutions is the link between Google video products and sales. Our mission is to fuel innovation that keeps YouTube and Video free and accessible to the world. We do this by translating global market needs into meaningful product solutions that drive business results for content partners and customers.

Responsibilities

Build, mentor, and inspire a team of data engineers in delivering scalable and reliable data solutions, fostering a culture of collaboration, innovation, and professional growth.
Develop, architect and optimize robust data pipelines, ensuring data quality, accuracy, and scalability to meet the evolving needs of the business.
Partner with cross-functional teams (marketing, data science, engineering, analytics) to build data models, automate processes, and unlock actionable insights that drive business decisions and results.
Collaborate with key stakeholders to shape the overall data strategy, advocating centralized data infrastructure that empowers reporting, analytics, and data science initiatives across the organization.
Mentor the team on data engineering best practices, ensuring adherence to industry standards and driving the development of solutions to address complex business challenges.