United States only- 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 diverse scope
where analysis of data requires evaluation of identifiable factors. - Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
- Telecommute from anywhere in the U.S. permitted (remote work benefit).
- Employer will accept a Bachelor’s degree in Computer Science, Engineering, Computer Information Systems, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field, and 5 years of work experience in the job offered or in a computer-related occupation. OR Employer will accept seven years of work experience in job offered or in a computer-related occupation. Any suitable combination of education, training, or experience is acceptable. Requires five years of experience in the following:
- 1. Features, design, and use-case scenarios across a big data or data warehouse ecosystem
- 2. Custom ETL design, implementation, and maintenance
- 3. Schema design and dimensional data modeling
- 4. Writing SQL statements
- 5. Analyzing data to identify deliverables, gaps, and inconsistencies
- 6. Managing and communicating data warehouse plans to internal clients
- 7. Python.
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.
Australia
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