MINIMUM QUALIFICATIONS

• Requires a Master’s degree(or foreign equivalent degree) in Computer Science, Engineering, Information Systems, Information Management, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field and one year of work experience in the job offered or in a computer-related occupation. Requires one year of experience in the following:
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• Features, design, and use-case scenarios across a big data ecosystem

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• Custom ETL design, implementation, and maintenance

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• Object-oriented programming languages

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• Schema design and dimensional data modeling

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• Writing SQL statements

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• Analyzing data to identify deliverables, gaps, and inconsistencies

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• Managing and communicating data warehouse plans to internal clients

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• MapReduce or MPP system

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• Python
  
  For those who live in or expect to work from California if hired for this position.

• 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.