Senior Product Analytics Data Engineer

Meta; Sacramento (CA); On-site; USD 177,000 - 247,000; Full time

Job summary

Meta is seeking a Data Engineer to shape data strategy for consumer and business products across its family of apps, including Facebook, Instagram, and WhatsApp. You will design scalable data architectures, build robust data models, and craft data-driven insights to guide product and growth decisions.

You will collaborate with software engineers, data scientists, and product managers to deliver end-to-end data solutions, optimize pipelines, and ensure data security and quality in a high-scale

Qualifications

• Bachelor's degree or equivalent technical experience.
• 7+ years in data roles (data engineer/scientist/analyst).
• 7+ years with SQL, ETL, data modeling and at least one programming language.

Responsibilities

• Conceptualize and own data architecture for large-scale projects.
• Develop logging frameworks and triage data infrastructure issues.
• Collaborate with engineers, PMs, and data scientists to surface insights.
• Define and manage SLAs for data sets under ownership.
• Design data security models aligned with privacy requirements.
• Build sophisticated data models and visualizations for multiple use cases.
• Solve complex ETL/data integration problems across sources.
• Optimize production code and data pipelines for efficiency.
• Mentor teammates and influence cross-functional teams.

Skills

Data architecture

SQL

ETL

Data modeling

Python

C++

Education

Bachelor's degree in Computer Science or related field

Master's or PhD preferred

Tools

ETL frameworks

Analytics dashboards

Job description

Meta is seeking a Data Engineer to shape data strategy for consumer and business products across its family of apps, including Facebook, Instagram, and WhatsApp. You will design scalable data architectures, build robust data models, and craft data-driven insights to guide product and growth decisions.

You will collaborate with software engineers, data scientists, and product managers to deliver end-to-end data solutions, optimize pipelines, and ensure data security and quality in a high-scale