applinity

Data Engineer

at Meta

Location

Menlo Park, CA

Type

full time

Posted

2 months ago

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Job description

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. To apply, click “Apply to Job” online on this web page.

Responsibilities

  • Perform data analysis to generate business insights.
  • Interface with Engineers, Product Managers and Product Analysts to understand product goals and data needs.
  • Build data expertise and own data quality for allocated areas of ownership.
  • Manage data warehouse plans for a product or a group of products.
  • Support critical data processes running in production.
  • Design and develop creative and innovative solutions to manipulate and transform data coming from diverse domains and components.
  • Leverage a homegrown Extract, Transform, Load (ETL) framework as well as off-the-shelf ETL tools, as appropriate.
  • Collaborate with data infrastructure and engineering teams to build and extend cross platform ETL and reports generation frameworks.
  • Provide consultation to business partners including analysts, managers, end users, and developers to clarify work objectives, determine project scope, obtain consensus, identify problems and recommend solutions.

Minimum Qualifications

  • Bachelor’s degree (or foreign degree equivalent degree) in Computer Science, Computer Software, Computer Engineering, Applied Sciences, Mathematics, Physics, or related field and 6 months of work experience in the job offered or a related occupation
  • Requires 6 months of experience in the following:
  • Programming knowledge in Python or Java
  • SQL
  • Database systems
  • Big Data systems
  • Analytics visualization concepts and tooling
  • Extract, Transform, and Load processes (ETL), and
  • Data architecture methodologies