Senior Data Engineer, Analytics & Platform

Meta; Dover (DE); On-site; USD 210,000 - 281,000; Full time

Job summary

Meta is seeking a technical leader for the Data Engineering team to shape the data foundation and analytics across platforms. You will work with product managers, data scientists, and software engineers to drive impact for billions of users and ensure scalable, secure data architectures.

You will own data architecture for large-scale projects, establish governance and security practices, mentor engineers, and influence cross-functional decisions with data-driven insights.

Qualifications

• Bachelor's degree in Computer Science, Engineering or equivalent.
• 10+ years in data warehouse space.
• 10+ years in custom ETL design and maintenance.
• 10+ years in OO programming.
• 10+ years in schema design and dimensional modeling.
• 10+ years in authoring SQL statements.
• Experience analyzing data to identify deliverables and gaps.
• Experience communicating data warehouse plans to internal clients.

Responsibilities

• Proactively drive vision for data foundation and analytics across platforms.
• Own data architecture for large-scale projects, evaluating design and cost-benefit tradeoffs.
• Create frameworks to improve data logging efficacy and triage issues.
• Build cross-functional relationships with data scientists, PMs and engineers.
• Define and manage SLAs for data sets in ownership areas.
• Implement security models compliant with privacy requirements and governance.

Skills

Data architecture

Cross-functional leadership

ETL design

SQL

Data governance

Mentoring

Education

Bachelor's degree in CS/Engineering or equivalent

Tools

MapReduce

MPP systems

Python

Job description

Meta is seeking a technical leader for the Data Engineering team to shape the data foundation and analytics across platforms. You will work with product managers, data scientists, and software engineers to drive impact for billions of users and ensure scalable, secure data architectures.

You will own data architecture for large-scale projects, establish governance and security practices, mentor engineers, and influence cross-functional decisions with data-driven insights.