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Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.
Job Responsibility:
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Define and manage SLA for all data sets in allocated areas of ownership
Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Solve our most challenging data integration problems, utilizing optimal ETL patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Influence product and cross-functional teams to identify data opportunities to drive impact
Design, build, and maintain regulatory compliance data processes in collaboration with legal counsel and policy managers
Mentor team members by giving/receiving actionable feedback
Requirements:
Requires a Master's degree (or foreign equivalent degree) in Computer Science, Computer Engineering, or a related field
Requires completion of graduate-level course, research project, internship, or thesis in the following: Custom ETL design, implementation, and maintenance
Object-oriented programming languages ( Python, C++, C#, or Scala)
Features, design, and use-case scenarios across a big data ecosystem
Schema design and dimensional data modeling
Writing SQL statements
Analyzing data to identify deliverables, gaps, and inconsistencies
Managing and communicating data warehouse plans to internal clients