MINIMUM QUALIFICATIONS

• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent
• 4+ years of experience where the primary responsibility involves working with data. This could include roles such as data analyst, data scientist, data engineer, or similar positions
• 4+ years of experience with SQL, ETL, data modeling, and at least one programming language (e.g., Python, C++, C#, Scala, etc.)

PREFERRED QUALIFICATIONS

• Master’s or Ph.D degree in a STEM field
  For those who live in or expect to work from California if hired for this position.

• Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
• Create and contribute to frameworks that improve the efficacy of logging 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 in a meaningful way
• Define and manage Service Level Agreements for all data sets in allocated areas of ownership
• 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
• Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
• Solve our most challenging data integration problems, utilizing optimal Extract, Transform, Load (ETL) patterns, frameworks, query techniques, sourcing from structured and unstructured data sources
• Assist in owning existing processes running in production, optimizing complex code through advanced algorithmic concepts
• 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
• Mentor team members by giving/receiving actionable feedback