Data Engineer, Product Analytics

Role overview

Data engineering and analytics

• Conceptualize and own data architecture for multiple large-scale projects; assess design and operational cost-benefit tradeoffs.
• Build frameworks that improve logging data and work with data infrastructure teams to triage and resolve issues.
• Collaborate with engineers, product managers, and data scientists to understand data needs and represent insights meaningfully.
• Define and manage dataset service-level agreements in areas of ownership.
• Establish security safeguards, resolve data-quality issues, and evolve governance processes.
• Build sophisticated data models and visualizations for multiple product and domain use cases.
• Solve data integration problems using ETL patterns, frameworks, and query techniques across structured and unstructured sources.
• Maintain production processes, optimize complex code, and improve pipelines, dashboards, frameworks, and systems.

Product impact and collaboration

• Use data to shape product development, identify opportunities, and help prioritize projects and solutions.
• Influence product and cross-functional teams to identify data opportunities and drive impact.
• Communicate data-driven stories, insights, and recommendations clearly to partners.
• Mentor team members by providing 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 roles such as data analyst, data scientist, or data engineer.
• At least 4 years of experience with SQL, ETL, data modeling, and at least one programming language; applicants with a Ph.D. may meet this requirement with at least 2 years of experience.

Preferred qualifications

• Experience implementing responsible and ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
• Ability to integrate AI tools into workflow redesign or optimization and demonstrate measurable impact.
• Ongoing AI skill development, including prompt/context engineering or agent orchestration, and awareness of emerging AI technologies.
• A master's or Ph.D. degree in a STEM field is preferred.

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