Data Engineer, Analytics

Meta, a global technology leader formerly known as Facebook, is seeking a Data Engineer for their Analytics team in New York. This role sits at the intersection of big data and business intelligence, requiring expertise in both technical implementation and strategic thinking.

The position involves designing and implementing sophisticated data warehousing solutions that drive informed decision-making across Meta's product suite. You'll work with massive datasets using distributed computing technologies and cloud infrastructure, creating data models and visualizations that support multiple use cases across different products and domains.

As a Data Engineer, you'll collaborate closely with engineers, product managers, and data scientists to understand and fulfill data needs. Your responsibilities will include managing ETL workflows, ensuring data quality and reliability, implementing security models, and maintaining privacy requirements. You'll also play a crucial role in supporting experimentation and machine learning initiatives by providing well-structured data sources.

The ideal candidate will have a Master's degree in a relevant field and strong technical skills in Python, SQL, and big data technologies. You'll need experience with ETL processes, dimensional data modeling, and distributed computing systems. The role offers competitive compensation ($182,583-$196,900/year) plus bonus, equity, and comprehensive benefits.

This is an excellent opportunity for a data professional who wants to work on challenging problems at scale, contributing to products that impact billions of users worldwide. You'll be part of Meta's journey beyond traditional social media into new frontiers like augmented and virtual reality, helping build the next evolution in social technology.

The role combines technical expertise with business impact, requiring someone who can both implement robust data solutions and understand their strategic importance. You'll work in a collaborative environment where you can influence product decisions and help shape the future of data engineering practices at Meta.