Join YouTube India as a Data Engineer and be instrumental in shaping the future of data-driven insights. This role focuses on building robust data products that power business operations, ensuring timely and accurate business intelligence for YouTube's vast ecosystem.

You'll be part of a dynamic team dedicated to democratizing YouTube's business data, empowering leaders with actionable insights. We focus on creating and maintaining efficient Extract, Transform, Load (ETL) systems, setting industry best practices for data management, and cultivating deep expertise across various data domains. Our collective goal is to enhance business efficiency and effectiveness through scalable centralized reporting.

Engage in requirements gathering and project scoping sessions with subject matter experts, business users, and executive stakeholders to precisely define business data needs.

Develop and maintain critical data platforms, ensuring data reliability, integrity, and governance for accurate, consistent, and trustworthy datasets.

Write and review essential end-user and technical documentation, including requirements and design specifications for current and future data systems, alongside data standards and policies.

Collaborate with the analyst community, understanding critical user journeys and data sourcing inefficiencies, while advocating for best practices and leading analyst training initiatives.

A Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience is required.

We seek candidates with 5 years of experience in data warehouses, distributed data platforms, and data lakes. Proficiency in software development using Java, C++, Python, Go, or JavaScript is essential.

Demonstrated experience in stakeholder management is also a key requirement for this role.

Preferred qualifications include experience with data warehouse architectures, ETL/ELT processes, and modern web technologies for building high-availability applications. Experience with Big Data, information retrieval, data mining, or machine learning is beneficial, as is the ability to thrive in a fast-paced, ambiguous environment with multiple stakeholders.