Data Engineer, Product Analytics

About the Role

As a Data Engineer at Meta, you will shape the future of people-facing and business-facing products across Meta's family of applications. Your technical skills and analytical mindset will be utilized designing and building some of the world's most extensive data sets, helping to craft experiences for billions of people and hundreds of millions of businesses worldwide. You will collaborate with software engineering, data science, and product management teams to design/build scalable data solutions to optimize growth, strategy, and user experience for billions of users and our internal employee community. You will be at the forefront of identifying and solving some of the most interesting data challenges at a scale few companies can match. By joining Meta, you will become part of a world-class data engineering community dedicated to skill development and career growth.

Data Engineering Responsibilities

• Guide teams by building optimal data artifacts (including datasets and visualizations) to address key questions.
• Refine systems, design logging solutions, and create scalable data models.
• Ensure data security and quality, with a strong focus on efficiency.
• Suggest architecture and development approaches and data management standards to address complex analytical problems.

Product Leadership Responsibilities

• Use data to shape product development, identify new opportunities, and tackle upcoming challenges.
• Ensure products add value for users and businesses by prioritizing projects and driving innovative solutions.

Communication and Influence Responsibilities

• Tell data-driven stories to convince and influence partners using clear insights and recommendations.
• Build credibility through structure and clarity, and be a trusted strategic partner.

Key Responsibilities

• Manage and execute data warehouse plans for a product or group of products to solve well-scoped problems.
• Identify the data needed for a business problem and implement logging required to ensure data availability, while working with data infrastructure to triage issues and resolve.
• Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way.
• Build data expertise and leverage data controls to ensure privacy, security, compliance, data quality, and operations for allocated areas of ownership.
• Design, build, and launch new data models and visualizations in production, leveraging common development toolkits.
• Independently design, build, and launch new data extraction, transformation, and loading processes in production, mentoring others around efficient queries.
• Support existing processes running in production and implement optimized solutions with limited guidance.
• Define and manage Service Level Agreements for data sets in allocated areas of ownership.

Requirements & Tech Stack

• SQL
• ETL
• Data Modeling
• At least one programming language (e.g., Python, C++, C#, Scala, or others).

Qualifications

• 2+ years of experience where the primary responsibility involves working with data (e.g., data analyst, data scientist, data engineer, or similar positions).
• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

Preferred Qualifications

• Master's or Ph.D degree in a STEM field.
• Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements).
• Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews).
• Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies.