Member of Data Staff (Analytics Engineer)
Perplexity1 month ago
Base Salary
$175k - $330k/yr
Responsibilities
- Design and maintain reliable data models, marts, and production pipelines.
- Help own warehouse architecture, environments, permissions, performance, costs, lifecycle, and operational hygiene.
- Build documentation, semantic context, metadata, lineage, and retrieval patterns that make warehouse data understandable to AI systems.
- Define and champion dbt, dimensional modeling, naming, testing, and review standards.
- Lead governance practices for ownership, access, lineage, documentation, retention, quality, and sensitive data handling.
- Build AI-assisted workflows for data quality detection, root-cause analysis, test generation, and maintenance automation.
- Improve data team tooling and productivity while partnering with data scientists, engineering, product, finance, and GTM teams.
- Evaluate build-versus-buy tradeoffs, choose scalable tools, and manage vendor relationships when needed.
Requirements
- 6+ years of experience as an analytics engineer, data engineer, data scientist, or closely related professional.
- Deep SQL expertise, including correctness, performance, joins, grain, and edge cases in complex warehouse queries.
- Hands-on production experience with dbt or a similar transformation framework, dimensional modeling, data contracts, testing, and evolving 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 data-access risks.
- Regular 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 and deliver production-quality systems with minimal oversight.
- Strong operational judgment around reliability, governance, security, cost, and maintainability.
- Snowflake administration or optimization, RBAC, PII handling, data classification, retention policies, audit workflows, privacy or security reviews, Databricks, semantic or metrics layers, metadata systems, data catalogs, and Python experience are preferred.
Benefits
- High-ownership role shaping the company's data foundation and company-wide defaults.
- Opportunity to build data infrastructure that serves both humans and AI agents.
- Small team with broad scope to define standards, choose tools, and ship high-leverage systems.
About Perplexity
Perplexity builds an AI-powered answer engine for web and mobile and an enterprise product, Perplexity Computer, for AI-driven workflows across tools and apps. The company monetizes through individual subscriptions (Perplexity Pro) and enterprise plans. Founded in 2022 and headquartered in San Francisco, it operates as a privately held company.