Data Engineer, Product Analytics

Role overview

Data engineering and product leadership

• Own data architecture for multiple large-scale projects and evaluate system design and operational cost-benefit tradeoffs.
• Improve logging frameworks, troubleshoot data infrastructure issues, and manage dataset service-level agreements.
• Build data models and visualizations, solve ETL and integration challenges, and maintain and optimize production processes.
• Implement privacy and security safeguards, improve data quality and governance, and optimize pipelines and dashboards.
• Use data to shape product development, identify opportunities, and communicate clear insights and recommendations.
• Influence cross-functional teams and mentor team members with actionable feedback.

Minimum qualifications

• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent.
• 4+ years of experience primarily working with data in roles such as data analyst, data scientist, or data engineer.
• 4+ years of experience with SQL, ETL, data modeling, and at least one programming language, or 2+ years with a Ph.D.

Preferred qualifications

• Experience implementing responsible, ethical AI practices, including risk assessment, bias mitigation, and quality reviews.
• Ability to integrate AI tools to improve workflows and produce measurable impact.
• Ongoing AI skill development, such as prompt or context engineering and agent orchestration.
• Master's or Ph.D. in a STEM field.

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