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Member of Data Staff (Analytics Engineer)

Perplexity· Data Science
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Hybrid (San Francisco), Hybrid (New York City)$175k - $330k + equityFull-timePosted 2w ago

About the role

Analytics engineer role focused on building a foundation for an AI-native data organization. Design core data models, pipelines, semantic layers, governance, and warehouse workflows to power the company with trusted data, while ensuring security and privacy for AI agents, data scientists, and stakeholders.

Responsibilities

  • 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 - 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 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.

Qualifications

  • 6+ years of experience as an analytics engineer, data engineer, data scientist, or closely related role.
  • Deep SQL expertise - ability to reason about correctness, performance, joins, grain, and edge cases in complex warehouse queries.
  • Strong data modeling experience - hands-on with dbt (or similar) in production; understanding of dimensional modeling, data contracts, testing, and evolving analytical schemas.
  • Pipeline ownership - built, maintained, debugged, and improved production data pipelines.
  • Warehouse management experience - warehouse administration, access patterns, permissions, performance tuning, cost management, or operational ownership.
  • Governance mindset - clear thinking about data ownership, access controls, privacy, retention, lineage, auditability, and risks of easy data access.
  • AI-native working style - using AI to speed up development, documentation, QA, exploration, and automation.
  • Stakeholder fluency - converting messy analytical requirements into trusted models, metrics, and reusable data assets.
  • Autonomy and execution - ability to take projects from ambiguity to production-quality systems with minimal oversight.
  • Operational judgment - focus on reliability, governance, security, cost, and long-term maintainability.

Skills

Required:SQLdbt / transformation frameworkData modelingData governance
Nice to have:AI-assisted tooling

Benefits

  • Full-time U.S. benefits including equity, health, dental, vision, retirement, fitness, commuter and dependent care accounts, and more.
  • International benefits tailored to region of residence.
Last updated Oct 7, 2026. Interested? Apply on the company site.

About Perplexity

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Company profileWebsite

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