Data Engineer, Analytics

$240,050 - $279,400/Yr

Meta - Salt Lake City, UT

Full-time - Mid Level

Remote - Salt Lake City, UT

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About the position

Meta Platforms, Inc. (Meta), formerly known as Facebook Inc., is at the forefront of building technologies that connect people, foster communities, and enhance business growth. Since its inception in 2004, Facebook has revolutionized the way individuals interact. With the introduction of applications and services such as Messenger, Instagram, and WhatsApp, Meta has empowered billions globally. As the company evolves, it is now focusing on immersive experiences, including augmented and virtual reality, to shape the future of social technology. The Data Engineer role is pivotal in this transformation, requiring a blend of technical expertise and collaborative spirit. The successful candidate will be responsible for designing, modeling, and implementing data warehousing activities that form the backbone of data-driven decision-making processes. This role involves creating sophisticated data models and visualizations that cater to various use cases across different products and domains. Collaboration is key, as the Data Engineer will work closely with engineers, product managers, and data scientists to understand data needs and present key insights visually. In addition to technical responsibilities, the Data Engineer will define and manage service level agreements (SLAs) for all data sets within their ownership. They will also contribute to frameworks that enhance data logging efficacy and work with data infrastructure to troubleshoot and resolve issues. Security is paramount; thus, the engineer will determine and implement security models based on privacy requirements, ensuring that safeguards are adhered to and addressing any data quality issues that arise. The role also involves solving complex data integration challenges using optimal ETL patterns and frameworks, as well as optimizing pipelines, dashboards, and systems to streamline the development of data artifacts. The Data Engineer will influence product and cross-functional teams to identify data opportunities that can drive significant impact, working on problems of moderate scope that require a comprehensive analysis of various factors. The position allows for telecommuting from anywhere in the U.S., providing flexibility in the work environment.

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.
• Work on problems of moderate scope where analysis of situations or data requires a review of a variety of factors.
• Exercise judgment within defined procedures and practices to determine appropriate action.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, Mathematics, Statistics, Data Science, or a related field.
• 60 months of progressive, post-baccalaureate experience in the job offered or in a computer-related occupation.
• Experience with features, design, and use-case scenarios across a big data ecosystem.
• Custom ETL design, implementation, and maintenance experience.
• Schema design and dimensional data modeling experience.
• Managing and communicating data warehouse plans to internal clients.
• Experience with MapReduce or MPP systems.
• Proficiency in Python.

Benefits

• Bonus
• Equity
• Health benefits