Senior Data Engineer, Machine Learning

Meta Meta · Big Tech · Menlo Park, CA

Meta is seeking a Senior Data Engineer specializing in Machine Learning to design, build, and optimize data warehousing and data pipelines. This role will focus on enhancing ML data infrastructure, supporting feed recommendations and ranking systems, and collaborating with ML engineers to develop analytics tools. The position requires a Master's degree and experience in data modeling, ETL, big data technologies, and data privacy.

What you'd actually do

  1. Design, model, and implement data warehousing activities to deliver the data foundation that drives impact through informed decision making.
  2. Design, build and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains.
  3. Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way.
  4. Define and manage SLA for all data sets in allocated areas of ownership.
  5. Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve.

Skills

Required

  • Designing interconnected components for end-to-end data management, including data collection, storage, integration, and utilization
  • Designing and building scalable data pipelines and ETL processes
  • Proficiency in object-oriented programming languages such as Python, PHP, and JavaScript
  • Big data technologies like MapReduce and Spark
  • SQL and experience with relational databases (e.g., MySQL, PostgreSQL)
  • Data modeling, data warehousing, and building data lakes
  • Analyzing data to identify deliverables, gaps, and inconsistencies
  • Developing solutions to complex data problems using programming and scripting languages
  • Data privacy and security best practices

Nice to have

  • Machine learning explainability
  • ML data infrastructure
  • Feed recommendations
  • Ranking systems

What the JD emphasized

  • Enhancing machine learning explainability and tracking mechanisms
  • Strengthening our foundational ML data infrastructure
  • Engage deeply in strategic growth areas for feed recommendations
  • Possess the ability to comprehend machine learning workflows and manage complex ranking systems that serve billions of users.

Other signals

  • ML data infrastructure
  • ranking systems
  • feed recommendations