Data Engineer, Product Analytics

Meta Meta · Big Tech · Los Angeles, CA +1

Data Engineer at Meta responsible for designing and building scalable data solutions across Meta's family of applications to optimize growth, strategy, and user experience. The role involves collaborating with software engineering, data science, and product management teams, managing data warehouse plans, implementing logging, designing data models and ETL processes, and ensuring data security and quality. The role also emphasizes using data to shape product development and communicate data-driven stories. While not core AI development, the role requires integrating AI tools to optimize workflows and demonstrating ongoing AI skill development.

What you'd actually do

  1. Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems
  2. Identify the data needed for a business problem and implement logging required to ensure availability of data, while working with data infrastructure to triage issues and resolve
  3. Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights in a meaningful way
  4. Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership
  5. Design, build and launch new data models and visualizations in production, leveraging common development toolkits

Skills

Required

  • SQL
  • ETL
  • data modeling
  • Python
  • C++
  • C#
  • Scala

Nice to have

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
  • Master's or Ph.D degree in a STEM field

What the JD emphasized

  • Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
  • Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
  • Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies