Perplexity
Perplexity
201 – 500 Employees
ConsultingHealthcareMarketing
Perplexity develops an AI-powered conversational search and assistant platform for researching questions in natural language. Its web-based product delivers concise, sourced responses and supports deeper exploration through curated Spaces covering topics such as Finance, Health, and Sports. Users can compare information, troubleshoot problems, analyze subjects, review search history, and access additional capabilities through a Pro subscription. The platform is designed for people seeking a faster way to investigate information and organize research across a range of topics.

Staff Analytics Engineer at Perplexity — San Francisco Hybrid

Perplexity is seeking a Staff Analytics Engineer to build reliable, governed data infrastructure for its AI-powered answer engine. The role covers warehouses, pipelines, semantic layers, and AI-readable data systems.

Description

  • Build and maintain dependable data models, marts, and pipelines
  • Help manage warehouse architecture, environments, permissions, performance, costs, lifecycle, and operational standards
  • Improve warehouse usability for AI through documentation, semantic context, metadata, lineage, and retrieval patterns
  • Establish and promote dbt practices, dimensional modeling standards, naming conventions, testing, and review workflows
  • Set data governance standards covering access, ownership, lineage, documentation, retention, quality, and sensitive information
  • Work with engineering, security, legal, and finance to enable secure, privacy-conscious data access and AI workflows
  • Develop AI-supported processes for detecting issues, explaining root causes, suggesting fixes, generating tests, and reducing reactive maintenance
  • Automate recurring tasks, enhance internal tooling, and improve data team efficiency
  • Collaborate with data science, engineering, product, finance, and go-to-market teams to turn analytical needs into durable systems
  • Assess build-versus-buy options, oversee vendors, and choose tools that can scale

Requirements

  • At least six years of experience in analytics engineering, data engineering, data science, or a closely related field
  • Advanced SQL skills, including query correctness, performance, joins, grain, and edge-case handling
  • Production experience with dbt or a comparable data transformation framework
  • Working knowledge of dimensional modeling, data contracts, testing, and analytical schema evolution
  • Experience building, operating, troubleshooting, and optimizing production data pipelines
  • Experience with warehouse administration, access patterns, permissions, performance tuning, cost control, or operational ownership
  • Knowledge of data ownership, access controls, privacy, retention, lineage, auditability, and sensitive-data risks
  • Experience applying AI to development, documentation, quality assurance, exploration, and workflow automation
  • Ability to convert analytical requirements into trusted models, metrics, and reusable data assets
  • Ability to lead projects from ambiguous problem definition through production delivery with limited oversight
  • Sound operational judgment around reliability, governance, security, cost, and maintainability
  • Ability to work from the office four days each week
  • The application asks whether you require U.S. work visa sponsorship

Benefits

  • Equity compensation
  • Health insurance coverage
  • Dental insurance coverage
  • Vision insurance coverage
  • Retirement benefits
  • Fitness benefits
  • Commuter benefits
  • Dependent care accounts
  • Benefits tailored by region for full-time employees outside the U.S.

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