Data Engineer, AI Analytics — Scalable Data Architect

Meta; Menlo Park (CA); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta in Menlo Park, CA is seeking a Data Engineer focused on analytics for Ranking and AI, on-site. You will own scalable data architectures, develop robust logging frameworks, and partner with engineers, product managers, and data scientists to capture data needs and translate insights into meaningful dashboards and visualizations across multiple products and domains.

You will help establish data governance and quality controls to drive trust and impact.

Qualifications

• 7+ years of experience with SQL.
• Experience with ETL.
• Experience with data modeling.
• Experience with at least one programming language (Python, C++, C#, Scala) or similar.

Responsibilities

• Own and design scalable data architectures for large-scale initiatives.
• Develop logging data frameworks and collaborate with infra teams.
• Partner with engineers, PMs, and data scientists to translate data needs into visualizations.
• Establish and manage SLAs for data sets within domains.
• Design security models aligned with privacy requirements and governance.
• Create, deploy, and launch data models and visualizations for multiple use cases.
• Address complex data integration with ETL patterns across sources.
• Assist in maintaining production data processes and optimize code performance.
• Refine pipelines, dashboards, frameworks, and systems to accelerate data artifacts.
• Influence cross-functional teams to uncover data opportunities and impact.
• Provide mentorship through actionable feedback.

Skills

SQL

ETL

Data modeling

Python

C++

C#

Scala

Education

Master's or PhD in STEM

Tools

SQL

ETL

Python

C++

C#

Scala

Job description

Meta in Menlo Park, CA is seeking a Data Engineer focused on analytics for Ranking and AI, on-site. You will own scalable data architectures, develop robust logging frameworks, and partner with engineers, product managers, and data scientists to capture data needs and translate insights into meaningful dashboards and visualizations across multiple products and domains.

You will help establish data governance and quality controls to drive trust and impact.