Data Engineer, Product Analytics

Role overview

Data engineering

• Own data architecture for large-scale projects and evaluate design and operating cost-benefit tradeoffs.
• Build logging frameworks, scalable data models, datasets and visualizations.
• Set dataset service-level agreements and implement privacy, security, quality and governance safeguards.
• Develop ETL solutions for structured and unstructured data sources and maintain production processes.
• Optimize pipelines, dashboards, frameworks, systems and complex code.

Product and team collaboration

• Work with engineering, product and data science partners to understand data needs and communicate insights.
• Influence cross-functional teams to identify data opportunities and inform product decisions.
• Mentor colleagues through actionable feedback.

Minimum qualifications

• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent.
• At least four years of experience primarily working with data.
• At least four years with SQL, ETL, data modeling and one programming language, or at least two years with a Ph.D.

Preferred qualifications

• Experience with responsible and ethical AI practices, including risk assessment, bias mitigation and quality reviews.
• Experience applying AI tools to improve workflows and measurable outcomes; ongoing AI development such as prompt engineering or agent orchestration.
• A master's or Ph.D. in a STEM field.

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