MINIMUM QUALIFICATIONS

• Requires a Bachelor’s degree (or foreign degree equivalent) in Computer Science, Engineering, Information Systems, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field and four years of work experience in the job offered or in a computer-related occupation. Requires four years of experience in the following:
• 
  
• Data ETL (Extract, Transform, Load) design, implementation, and maintenance on a large scale

• 
  
• Programming in Python, Perl, Java, Javascript, or PHP

• 
  
• Writing SQL statements

• 
  
• Analyzing large volumes of data to identify deliverables or to provide data driven insights, gaps, and inconsistencies

• 
  
• Data warehousing architecture and plans

• 
  
• Informatica, Talend, Pentaho, dimensional data modeling, or schema design.
  
  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 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.
• Telecommute from anywhere in the US permitted.