Data Engineer, Global YouTube Marketing

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 3 years of experience coding in one or more programming languages.
  
• 3 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
  
• 3 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (DataFlow, Spark, etc.).
  

Preferred qualifications:

• 3 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms.
  
• 3 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.
  
• 3 years of experience developing project plans and delivering projects on time within budget and scope.
  
• Experience with Machine Learning for production workflows.
  
• Understanding of incrementality measurement methodologies and frameworks
  

As a Data Infrastructure Manager for the Global YouTube Marketing team, you will be a key driver in 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 cutting-edge data solutions, design insightful dashboards, and establish robust data pipelines that fuel our marketing efforts. In this role, you will enable the marketing team to make data-driven decisions that optimize campaigns and quantify the incremental impact of marketing initiatives.Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

• Design and build data processing systems with a particular emphasis on security, compliance, scalability, efficiency, reliability, and portability.
  
• Create or consult in creating data visualizations using Business Intelligence (BI) tools (e.g., Datastudio, Tableau, etc.).
  
• Develop and maintain data models, pipelines, and exchange formats to assist in the visualization, analysis, and interpretation of data and for use of data in machine learning training/models.
• Provide ongoing support for data users through maintenance of reports, queries, and dashboards, fielding user questions, authoring documentation, and delivering training.
  
• Collaborate with cross-functional teams (e.g., Marketing, Data Science, Engineering, and Analytics) to understand data requirements and deliver impactful data solutions.