Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps and services like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. To apply, click “Apply to Job” online on this web page.
Responsibilities
- Design, model, and implement data warehousing activities to deliver the data foundation that drives impact through informed decision making.
- Design, build and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains.
- Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way.
- Define and manage SLA for all data sets in allocated areas of ownership.
- Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve.
- Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership.
- Solve challenging data integration problems utilizing optimal ETL patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
- Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.
- Influence product and cross-functional teams to identify data opportunities to drive impact.
- Address diverse problems where data analysis requires evaluating identifiable factors.
- Innovate new ideas, techniques, or processes to address challenges or seize opportunities.
- Seek clarity on goals and priorities to ensure swift progress, escalating issues as needed to remove obstacles.
- Identify, prioritize, and achieve clear short, mid, and long-term goals aligned with business objectives, keeping the team focused on delivering results.
- Help Meta meet legal and regulatory obligations and make decisions that reflect our mission, values, and principles.
- Play a key role in enhancing machine learning explainability and tracking mechanisms.
- Strengthen our foundational ML data infrastructure to broaden analytical capabilities.
- Engage deeply in strategic growth areas for feed recommendations, a crucial driver of Meta's revenue.
- Possess the ability to comprehend machine learning workflows and manage complex ranking systems that serve billions of users.
- Collaborate daily with software and ML engineers to understand their workflows and develop analytics tools that enhance system and process insights.
Minimum Qualifications
- Master's degree (or foreign degree equivalent) in Computer Science, Engineering, Information Systems, Mathematics, Statistics, Analytics, Data Analytics, Data Science, Applied Sciences, or a related field and 1 year of work experience in the job offered or in an analytics or computer-related occupation
- Requires 1 year of experience in the following:
- Designing interconnected components for end-to-end data management, including data collection, storage, integration, and utilization
- Designing and building scalable data pipelines and ETL processes
- Proficiency in object-oriented programming languages such as Python, PHP, and JavaScript
- Big data technologies like MapReduce and Spark
- SQL and experience with relational databases (e.g., MySQL, PostgreSQL)
- Data modeling, data warehousing, and building data lakes
- Analyzing data to identify deliverables, gaps, and inconsistencies
- Developing solutions to complex data problems using programming and scripting languages, employing parameterization and inheritance for reuse, and using tools like type systems, unit tests, and random testing to ensure program integrity, and
- Data privacy and security best practices