Meta Platforms, Inc. (Meta) is looking to enhance its machine learning capabilities by strengthening its foundational ML data infrastructure and improving machine learning explainability and tracking mechanisms. The goal is to broaden analytical capabilities and support strategic growth areas like feed recommendations, which are crucial for Meta's revenue.
Requirements
- 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
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.
Other
- 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 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
- Requires 1 year of experience in data privacy and security best practices
- Collaborate with engineers, product managers and data scientists to understand data needs
- Influence product and cross-functional teams to identify data opportunities to drive impact.
