Data Engineer, Analytics

This role provides technical leadership for analytics engineering work focused on strengthening Meta’s data foundation and analytics platform across major products, including Instagram. You will own key aspects of data architecture, governance for data marts, and end-to-end analytics systems, partnering with cross-functional stakeholders to deliver reliable data products.

Responsibilities

• Drive the vision for the data foundation and analytics platform to accelerate the design and improvement of cross-platform components across Instagram, including defining and executing an implementation plan.
• Conceptualize and own data architecture for multiple large-scale initiatives, assessing design options and operational cost-benefit tradeoffs within production systems.
• Develop and contribute to frameworks that improve logging data effectiveness, and collaborate with data infrastructure teams to triage issues and help resolve them.
• Build working relationships with Data Scientists, Product Managers, and Software Engineers to understand data needs and deliver required datasets and systems.
• Define and manage service level agreements (SLAs) for datasets in assigned ownership areas.
• Determine and implement security models aligned to privacy requirements, verify that safeguards are followed, address data quality issues, and evolve governance processes within assigned areas of ownership.
• Design, build, and launch collections of advanced data models and visualizations that support use cases across different products or domains.
• Solve difficult data integration problems using effective ETL patterns, frameworks, and query techniques across structured and unstructured data sources.
• Support ownership of existing production processes, optimizing complex code using advanced algorithmic concepts.
• Optimize pipelines, dashboards, frameworks, and systems to streamline the development of new data artifacts.
• Influence product and cross-functional teams to identify data opportunities and drive measurable impact.
• Mentor team members by providing and receiving actionable feedback.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
• 10+ years of experience in the data warehouse space.
• 10+ years of experience designing, implementing, and maintaining custom ETL.
• 10+ years of experience with object-oriented programming languages.
• 10+ years of experience with schema design and dimensional data modeling.
• 10+ years of experience writing SQL statements.
• Experience analyzing data to identify deliverables, gaps, and inconsistencies.
• Experience planning and communicating data warehouse roadmaps to internal clients.

Technologies

• SQL
• Python

Preferred Qualifications

• BS/BA in a Technical Field, Computer Science, or Mathematics.
• Experience working with either MapReduce or an MPP system.
• Experience working autonomously in global teams.
• Experience influencing product decisions using data.
• Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact (such as efficiency gains and quality improvements).
• Experience adhering to and implementing responsible, ethical AI practices, including risk assessment, bias mitigation, and quality and accuracy reviews.
• Demonstrated ongoing AI skill development (such as prompt/context engineering and agent orchestration) and staying current with emerging AI technologies.

Compensation and Location

• Salary range: USD 210,000 - 281,000 per year.
• Location: Remote.

Benefits

• Bonus
• Equity
• Benefits