Data Engineer, YouTube Marketing

Key Skills

Apache Hadoop, Big Data Technology, Data Engineering, Data science techniques, Google Dataflow, Infrastructure as code, Marketing Strategy, SPARK Programming

Job Description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 3 years of experience in an investigative role (e.g., media analytics, advertising sales, consulting, or financial analysis).
• Experience with coding, relational databases, SQL queries, database definitions, and schema design.
• 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 (e.g., DataFlow, Spark, etc.).

Preferred qualifications:

• Experience supporting client-side media and marketing data science.
• Experience with big data technologies (e.g., Hadoop, Spark).
• Experience in a non-technical stakeholder-facing role.
• Understanding of incrementality measurement methodologies and frameworks.
• Ability to be proactive and flexible to operate in a changing, constantly evolving and collaborative environment.

About the job

In this role, you will play a vital role in building and maintaining the data infrastructure that fuels our marketing strategy. You will design, develop, and optimize data pipelines, ensuring data quality and accessibility for advanced analytics. You will enable the marketing team to leverage data-driven insights to optimize campaigns and measure the 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.

Responsibilities

• Design, develop, and maintain scalable and reliable data pipelines to collect, process, and store data from various data sources.
• Implement data quality checks and monitoring to ensure data accuracy and integrity.
• Collaborate with cross-functional teams (e.g., marketing, data science, engineering, analytics) to understand data requirements and deliver impactful data solutions.
• Optimize data infrastructure for performance, efficiency, and scalability to meet evolving business needs.
• Create and maintain dashboards and reports to provide actionable insights to the marketing team.