Member Of Data Staff (Analytics Engineer)

Details

Perplexity is building an AI-native data organization. This role will design and maintain the data models, pipelines, semantic layers, data quality systems, governance practices, and warehouse workflows that support company-wide decision-making and operations. The role operates across analytics engineering, data engineering, data governance, and internal data products, with a focus on secure, privacy-aware, and AI-readable data systems.

Responsibilities

• Design and maintain high-quality data models, marts, and pipelines.
• Help own warehouse architecture, environments, permissions, performance, cost, data lifecycle, and operational hygiene.
• Maintain documentation, semantic context, metadata, lineage, and retrieval patterns so AI systems can correctly understand and query company data.
• Define and champion dbt patterns, dimensional modeling practices, naming conventions, tests, and review processes.
• Establish standards for data access, ownership, lineage, documentation, retention, quality, and sensitive data handling.
• Partner with engineering, security, legal, and finance to ensure data access, sharing, and AI-enabled workflows are controlled appropriately.
• Build AI-assisted data quality and maintenance workflows that detect issues, explain root causes, suggest fixes, generate tests, and reduce manual firefighting.
• Automate repetitive workflows, improve tooling, streamline development, and help data scientists and stakeholders answer questions more efficiently.
• Partner with data scientists, engineering, product, finance, and go-to-market teams to translate analytical needs into durable data systems.
• Evaluate build-versus-buy tradeoffs, manage vendor relationships when needed, and choose scalable tools.

Requirements

• 6+ years of experience as an analytics engineer, data engineer, data scientist, or in a closely related role.
• Deep SQL expertise, including correctness, performance, joins, grain, and edge cases in complex warehouse queries.
• Strong hands-on production experience with dbt or a similar transformation framework.
• Understanding of dimensional modeling, data contracts, testing, and the evolution of analytical schemas.
• Experience building, maintaining, debugging, and improving production data pipelines.
• Experience with warehouse administration, access patterns, permissions, performance tuning, cost management, or operational ownership.
• Understanding of data ownership, access controls, privacy, retention, lineage, auditability, and the risks of excessive data accessibility.
• An AI-native working style, including use of AI for development, documentation, quality assurance, exploration, and workflow automation.
• Ability to translate ambiguous analytical requirements into trusted models, metrics, and reusable data assets.
• Ability to take projects from ambiguous problem to production-quality system with minimal oversight.
• Strong judgment around reliability, governance, security, cost, and long-term maintainability.

Bonus Qualifications

• Snowflake administration, optimization, cost management, or warehouse performance tuning.
• Experience with RBAC, PII handling, data classification, retention policies, audit workflows, or privacy and 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.
• Experience as an early analytics engineer or data engineer at a high-growth startup.

Why This Role

• Own the data foundation that determines how quickly and confidently the company can use data.
• Build data infrastructure that is understandable by both AI agents and analysts.
• Create high-leverage models, pipelines, and tools for data scientists and stakeholders.
• Work on a small team with broad scope to define standards, choose tools, and ship company-wide systems.

Benefits

Full-time U.S. employees receive benefits including equity, health, dental, vision, retirement, fitness, commuter and dependent care accounts, and more. International employees receive benefits tailored to their region of residence. USD salary ranges apply only to U.S.-based positions; international salaries are based on the local market.