Data Engineer

Data Engineer

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
• 3 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
• Experience managing client-facing projects, troubleshooting technical issues, and working with engineering and sales services teams.
• Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.

Preferred qualifications:

• Master’s degree in Computer Science, Engineering, Statistics, or Mathematics.
• Experience with data warehouses, large-scale distributed data platforms, and data lakes.
• Ability to break down complex, multi-dimensional problems with structured thinking.
• Ability to navigate ambiguity in a fluid environment with multiple stakeholders.
• Excellent business and technical communication, organizational, and investigative skills.

About the job

As a Data Engineer, you will guide customers on how to ingest, store, process, analyze, explore, and visualize data on Google Cloud Platform. You will lead data migrations and transformations, partner with clients to architect scalable data processing systems, build efficient data pipelines, and resolve platform challenges. In this role, you'll collaborate with Google's strategic cloud customers and our team to successfully implement Google Cloud products.At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.

Responsibilities

• Conduct requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to discover and define business data needs.
• Design, build, and optimize the data architecture and extract, transform, and load (ETL) pipelines to make them accessible for Business Data Analysts, Data Scientists, and business users to enable data-driven decision-making.
• Work closely with analysts to productionize and scale value-creating capabilities, including data integrations and transformations, model features, and statistical and machine learning models.
• Drive the highest standards in data reliability, data integrity, and data governance, enabling accurate, consistent, and trustworthy data sets, business intelligence products, and analyses.
• Write and review end-user and technical documents, including requirements and design documents for existing and future data systems, as well as data standards and policies.

Experience Level

Mid Level