Member of Data Staff (Analytics Engineer)

Perplexity; United States; Remote; USD 110,000 - 170,000; Full time

Job summary

Perplexity seeks a middle-level Analytics Engineer to develop robust data systems that enhance decision-making. You will build and maintain the core data foundation, focusing on architecture, performance, and operational hygiene to support scalable data access.

You will lead data governance practices, establishing standards for data access and quality while ensuring that the warehouse is AI-readable and ready for AI integrations.

Qualifications

• Strong SQL and data modeling experience.
• Experience implementing data governance policies and standards.
• Ability to design data warehouses that support AI workloads.

Responsibilities

• Build and maintain the core data foundation for Perplexity, ensuring reliable data models and pipelines.
• Manage the data warehouse architecture, performance, and operational hygiene for scalable data access.
• Lead data governance practices, establishing standards for data access and quality while ensuring AI-readiness of the warehouse.
• Collaborate with cross-functional teams to empower stakeholders to leverage data effectively for humans and AI systems.

Skills

SQL

Data Modeling

Data Governance

AI Integration

Job description

Perplexity is seeking a middle-level Analytics Engineer to develop robust data systems that enhance decision-making. Ideal candidates will have deep SQL and data modeling expertise, with a focus on governance and AI integration.

In this role, you will build and maintain the core data foundation for Perplexity, ensuring that data models and pipelines are reliable and efficient. You will manage the data warehouse, focusing on architecture, performance, and operational hygiene to support scalable data access.

You will lead data governance practices, establishing standards for data access and quality while ensuring that the warehouse is AI-readable. Collaborating closely with various teams, your work will empower stakeholders to leverage data effectively, making it both usable for human analysts and compatible with AI systems.