Data Engineer, Product Analytics

Based in New York, NY on site, Meta's Data Engineer, Product Analytics designs scalable data solutions, guides data architecture, and delivers data driven insights to shape product development across Meta apps.

Responsibilities

• Own and design data architecture across several large scale initiatives, weighing design options against cost and operational trade offs.
• Develop and contribute to data logging frameworks to improve data capture, and triage issues with data infrastructure to resolve them.
• Partner with engineers, product managers, and data scientists to identify data needs and present key insights in clear, actionable formats.
• Establish and manage service level agreements for data sets within assigned domains.
• Define and implement security models aligned with privacy requirements, ensure safeguards are followed, address data quality issues, and evolve governance processes in owned areas.
• Design, build, and deploy advanced data models and visualizations that support multiple use cases across products and domains.
• Address complex data integration challenges using effective ETL patterns, frameworks, and query techniques across structured and unstructured sources.
• Support ownership of production processes and optimize complex code using advanced algorithmic concepts.
• Optimize pipelines, dashboards, frameworks, and systems to streamline the development of data artifacts.
• Influence product and cross functional teams to identify data opportunities that drive measurable impact.
• Provide mentorship through actionable feedback to team members.

Requirements

• Bachelor's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.
• Four or more years of hands on data work experience in roles such as data analyst, data scientist, data engineer, or similar.
• Four or more years of experience with SQL, ETL, data modeling, and proficiency in at least one programming language (for example Python, C++, C#, or Scala).

Technologies

• SQL
• Python
• C++
• C#
• Scala

Preferred Qualifications

• Master's or PhD degree in a STEM field.
• Experience integrating AI tools to optimize workflows and drive measurable impact.
• Experience applying responsible, ethical AI practices, including risk assessment, bias mitigation, and quality reviews.
• Active development of AI skills, such as prompt engineering and agent orchestration, and staying current with emerging AI technologies.