- Design, model, or implement data warehousing activities in order to contribute to the design and development of Meta products.
- Manage and execute data warehouse plans for a product or a group of products to solve well-scoped problems.
- Identify the data needed for a business problem and implement logging required to ensure availability of data, 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 visually 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 creating efficient queries.
- Support existing processes running in production and implement optimized solutions with limited guidance.
- Define and manage SLA for data sets in allocated areas of ownership.
- 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.
- Requires a Master's degree in Computer Science, Engineering, Information Systems, Statistics, Data Analytics, Mathematics, Applied Sciences, or a related field.
- Requires completion of a graduate-level course, research project, or internship in the following:
- 1. Data Visualization using Tableau, R, Python, or PowerBl
- 2. Legacy Data Migration
- 3. Database systems including relational, distributed, NoSQL, and/or object databases
- 4. Custom ETL design, implementation, and maintenance
- 5. Object-oriented programming languages
- 6. Schema design and dimensional data modeling
- 7. Writing SOL statements
- 8. Analyzing data to identify deliverables, gaps, and inconsistencies
- 9. Managing and communicating data warehouse plans to internal clients
- 10. MapReduce or MPP system and
- 11. Programming in Python.
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