Data Engineer, Product Analytics

Role overview

Responsibilities

• Own data architecture for multiple large-scale projects and evaluate design and operational cost-benefit tradeoffs.
• Improve logging frameworks and coordinate with data infrastructure teams to resolve issues.
• Partner with engineers, product managers, and data scientists to understand needs and communicate data insights.
• Define and manage dataset service-level agreements for owned areas.
• Implement privacy-based security models, safeguards, data quality improvements, and governance processes.
• Build sophisticated data models and visualizations for different products and domains.
• Solve data integration problems using ETL patterns and structured or unstructured sources.
• Support production processes and optimize complex code using advanced algorithmic concepts.
• Optimize pipelines, dashboards, frameworks, and systems.
• Identify data opportunities with product and cross-functional teams, and mentor colleagues with actionable feedback.

Minimum qualifications

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

Preferred qualifications

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

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