Data Engineer, Product Analytics

Meta offers a remote Data Engineer role focused on product analytics with a compensation range of USD 147,000 to 208,000 per year. You will collaborate with engineers, data scientists, and product managers to design scalable data architectures and visualizations that inform decisions across billions of users, supporting growth, strategy, and user experience.

Benefits

• Bonus
• Equity
• Benefits

Responsibilities

• Lead and own the data architecture for multiple large scale projects, weighing design choices against cost-benefit tradeoffs.
• Develop and contribute to frameworks that improve logging data, partnering with data infrastructure to triage and resolve issues.
• Collaborate with engineers, product managers, and data scientists to identify data needs and present key insights in meaningful formats.
• Define and manage service level agreements for datasets within your ownership.
• Establish security models aligned with privacy requirements, ensure safeguards are followed, address data quality issues, and evolve governance within your scope.
• Design, build, and deploy sophisticated data models and visualizations to support multiple use cases across products or domains.
• Tackle complex data integration challenges using effective ETL patterns, frameworks, and query techniques from structured and unstructured sources.
• Support ownership of existing production processes and optimize code with advanced algorithmic concepts.
• Improve pipelines, dashboards, frameworks, and systems to streamline the development of data artifacts.
• Influence product and cross-functional teams to uncover data opportunities that drive impact.
• Mentor colleagues through actionable feedback and collaborative guidance.

Requirements

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

Technologies

• SQL
• Python
• C++
• C#
• Scala
• ETL

Preferred Qualifications

• Master's or PhD in a STEM field
• Proven ability to integrate AI tools to optimize workflows and drive measurable impact
• Experience applying responsible, ethical AI practices, including risk assessment, bias mitigation, and quality checks
• Demonstrated ongoing AI skill development and familiarity with emerging AI technologies