---
title: 'Member of Data Staff (Analytics Engineer) at Perplexity'
canonical: 'https://feeny.ai/job/member-of-data-staff-analytics-engineer-perplexity-san-francisco-kdn82m1g87yr'
type: 'job'
last_seen: '2026-09-06'
---

# Member of Data Staff (Analytics Engineer) at Perplexity

- **Company:** [Perplexity](https://feeny.ai/companies/perplexity)
- **Location:** San Francisco, CA
- **Compensation:** $175k–$330k
- **Employment:** full-time
- **Posted:** 2026-02-20
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/Perplexity/fed8d2c4-9c82-43ad-a168-434146c759ff/application

**Skills:** SQL, Python, dbt, Data Modeling, Data Warehousing, APIs, LLMs, A/B Testing, Pipeline Management, Snowflake Administration, Snowflake Optimization, Slack Bots, Internal CLI Tools, AI Agent Frameworks, BI Tools

> Build AI-native data workflows, autonomous analytics agents, and scalable data infrastructure. The role involves transforming existing AI-driven workflows into repeatable systems, automating the data lifecycle, and creating self-healing pipelines to support a growing data team.

## Job description

Perplexity is AI for people who expect more. On the data team, that means building the systems that make our data reliable, understandable, and usable by both humans and AI.

We're looking for an analytics engineer or data engineer who wants to build the foundation for an AI-native data organization. You'll design core data models, pipelines, semantic layers, data quality systems, governance practices, and warehouse workflows that power the entire company: helping teams make strategic decisions, operate the business, and move faster with trusted data. You'll also make sure those systems are secure, privacy-aware, and legible to AI agents, data scientists, and the rest of the company.

This role is for someone who can operate at the boundary of analytics engineering, data engineering, data governance, and internal product. You care about dimensional modeling, dbt standards, cost-aware warehouse design, access controls, privacy, and the details that make data trustworthy. You also believe AI should make the data stack faster, easier to maintain, and more accessible across the company without weakening security or governance.

## WHAT YOU'LL DO

- Build the core data foundation - design and maintain high-quality data models, marts, and pipelines that make analysis fast, reliable, and reusable.
- Manage the data warehouse - help own warehouse architecture, environments, permissions, performance, cost, data lifecycle, and operational hygiene so the platform scales cleanly.
- Make the warehouse AI-readable - own the documentation, semantic context, metadata, lineage, and retrieval patterns that AI systems depend on to understand and query Perplexity's data correctly.
- Own data modeling standards - define and champion dbt patterns, dimensional modeling practices, naming conventions, tests, and review processes.
- Lead data governance practices - define standards for access, ownership, lineage, documentation, retention, quality, and sensitive data handling across the analytical warehouse.
- Build with security and privacy in mind - partner with engineering, security, legal, and finance where needed to ensure data access, sharing, and AI-enabled workflows are appropriate and controlled.
- Automate data quality and maintenance - build AI-assisted workflows that detect issues, explain root causes, suggest fixes, generate tests, and reduce manual firefighting.
- Improve data team productivity - automate repetitive workflows, improve tooling, streamline development, and make it easier for data scientists and stakeholders to answer questions.
- Partner across the company - work closely with data scientists, engineering, product, finance, and GTM teams to translate analytical needs into durable data systems.
- Shape tooling decisions - evaluate build-versus-buy tradeoffs, manage vendor relationships when needed, and choose tools that scale with the team.

## WHAT WE'RE LOOKING FOR

- 6+ years of experience as an analytics engineer, data engineer, data scientist, or closely related role.
- Deep SQL expertise - you can reason about correctness, performance, joins, grain, and edge cases in complex warehouse queries.
- Strong data modeling experience - you've worked hands-on with dbt (or a similar transformation framework) in production, and you understand dimensional modeling, data contracts, testing, and how analytical schemas should evolve.
- Pipeline ownership - you've built, maintained, debugged, and improved production data pipelines.
- Warehouse management experience - you've worked with warehouse administration, access patterns, permissions, performance tuning, cost management, or operational ownership.
- Governance mindset - you think clearly about data ownership, access controls, privacy, retention, lineage, auditability, and the risks of making data too easy to access.
- AI-native working style - you already use AI to speed up development, documentation, QA, exploration, and repetitive workflow automation.
- Stakeholder fluency - you know how to turn messy analytical requirements into trusted models, metrics, and reusable data assets.
- Autonomy and execution - you can take projects from ambiguous problem to production-quality system with minimal oversight.
- Operational judgment - you care about reliability, governance, security, cost, and long-term maintainability.

## BONUS

- Snowflake administration, optimization, cost management, or warehouse performance tuning.
- Experience with RBAC, PII handling, data classification, retention policies, audit workflows, or privacy/security reviews.
- Experience with Databricks or other modern data infrastructure.
- Experience building semantic layers, metrics layers, metadata systems, or data catalogs.
- Python experience for data tooling, automation, orchestration, or quality checks.
- Previous experience as an early analytics engineer or data engineer at a high-growth startup.

## WHY THIS ROLE

- Own the foundation - your work will determine how fast and confidently the company can use data.
- Build for humans and AI - the next generation of data infrastructure needs to be understandable by agents as well as analysts.
- High leverage - better models, pipelines, and tools multiply every data scientist and every stakeholder who depends on data.
- Small team, broad scope - you'll have room to define standards, choose tools, and ship systems that become company-wide defaults.

## About Perplexity

## Company Overview
- **One-liner**: Perplexity builds an AI-powered answer engine that delivers accurate, real-time answers to any question, serving curious minds and professionals who demand precision and speed.
- **Entity Type**: Private (total funding $1.7B across 16 rounds)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2022
- **Founders**: Aravind Srinivas, Denis Yarats, Johnny Ho, Andy Konwinski

## Core Business
- **Primary industry**: AI-powered search and knowledge retrieval, Software Development
- **Target customers**: B2C (general users), B2B (enterprise API customers), and power users seeking reliable information
- **Mission**: “AI for people who expect more – more accuracy, more agency, more signal, less noise.”

## Products & Services
- **Perplexity AI (Free Tier)**: Real-time conversational search engine that synthesizes web results with citations, accessible via web and mobile app. *Type*: SaaS
- **Perplexity Pro**: Subscription offering enhanced features such as advanced AI models, multimodal search, and increased usage limits. *Type*: SaaS (subscription)
- **Perplexity API Platform**: Enables developers to integrate Perplexity’s search and reasoning capabilities into their own applications. *Type*: API
- **Perplexity Browser Extension**: Brings AI-powered search directly into the browser for quick answers without leaving the page. *Type*: Browser extension

## Market Standing
- **Valuation/Market Cap**: Not publicly available in provided sources (prior reports indicate ~$9B valuation as of 2024, but not confirmed in this data set)
- **Key Metric**: Total funding $1.7B (16 rounds); annual revenue ~$50M (LinkedIn estimate)
- **Notable Investors/Partners**: Not explicitly listed in provided search results; widely known investors include IVP, NEA, Jeff Bezos, and others (not sourced here)
- **Growth Signals**: Headcount grew 11.3% YoY to 1,152 employees; operates in 54 countries; LinkedIn followers grew 131.8% yearly to >1.6M; active hiring across 48+ open roles including AI Research, Engineering, and Go-to-Market teams

## Competitive Advantages
- **Real-time, cited answers**: Unlike traditional chatbots, Perplexity grounds answers in live web results with transparent sources, building trust and accuracy.
- **Multimodal and agentic capabilities**: Continuously pushes frontier research (e.g., query-aware context compression, agents for knowledge work) that differentiates from generic LLM interfaces.
- **Vertical integration from research to product**: In-house AI research team tackles open problems unique to Perplexity’s scale, enabling fast iteration on novel methods.
- **Strong brand and user base**: Rapid consumer adoption with millions of monthly active users and high engagement.

## Strategic Focus
- **Pushing the frontier of search**: Evolving from retrieval services to code generation, agents, and full autonomy in knowledge work.
- **Expanding enterprise and API revenue**: Growing B2B footprint with API platform and enterprise solutions.
- **Global hiring and office expansion**: Offices in San Francisco, Palo Alto, New York, Austin, Washington D.C., London, Berlin, and Belgrade, with “4 days in office” hybrid model.
- **Investing in AI research**: Dedicated research division (Perplexity Research) exploring reasoning, agents, and systems to redefine how people navigate the internet.

## Why Work Here
- **Culture & Environment**: “Thoughtful support” culture with emphasis on craftsmanship, ownership, entrepreneurship, scholarship, and partnership. Hybrid schedule (4 days in-office) based on location.
- **Perks**: Daily catered meals (breakfast, lunch, dinner in office), office snacks, ride home program, commuter benefits, home office reimbursement, fitness classes, gym memberships.
- **Compensation & Benefits**: Competitive salary and equity packages; retirement plans with company match; flexible PTO; holiday shutdown between Christmas and New Year; 12 weeks paid bonding leave; comprehensive health, dental, and vision insurance.
- **Relocation & Visa Support**: Relocation assistance and visa/green card sponsorship for eligible roles. Partners with immigration firm to support the process.
- **Engineering Excellence**: “Technical assessment for relevant roles”; values hands-on contribution, broad skill sets, and merit-based evaluation. Frequent Tech Talks and exposure to greenfield AI research problems.

## Sources
1. [perplexity.ai/hub/careers](https://www.perplexity.ai/hub/careers)
2. [jobs.ashbyhq.com/perplexity](https://jobs.ashbyhq.com/perplexity)
3. [perplexity.ai](https://www.perplexity.ai/)
4. [linkedin.com/company/perplexity-ai](https://www.linkedin.com/company/perplexity-ai)
5. [research.perplexity.ai](https://research.perplexity.ai/)

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