Analytics Engineer
Role Overview
This senior-level Analytics Engineer role involves designing and building core data models to improve analysis efficiency, championing data modeling standards using tools like dbt, and automating workflows to boost team productivity. The hire will own tooling decisions, partner with Data Scientists, and lead data governance efforts, directly impacting business decisions and data reliability at Perplexity. As the second Analytics Engineer, they will play a key role in shaping the analytics infrastructure in a fast-paced, scaling environment.
Perks & Benefits
The job is fully remote, offering flexibility in location, though the company is headquartered in San Francisco with a hybrid schedule for in-office employees, implying potential collaboration during Pacific Time hours. Career growth is highlighted by the role's impact on defining analytics infrastructure and being an early hire in a high-growth startup, with a focus on autonomy and minimal oversight. Benefits likely include typical tech perks such as competitive compensation and opportunities for professional development in a mission-driven, knowledge-centric company culture.
Full Job Description
As our second Analytics Engineer, you’ll be instrumental in defining and building our analytics infrastructure, ensuring data is reliable, accessible, and drives critical business decisions across the company. You’ll play a key role in shaping how we use data at Perplexity, contributing directly to our mission of becoming the world’s most knowledge-centric company.
Perplexity is building the next-generation answer engine, empowering our users to find information more effectively. We are headquartered in San Francisco, and on a hybrid schedule with in-office days on Monday, Wednesday, Friday.
Responsibilities
Design and build core data models to improve analysis efficiency, enabling rapid, reliable insights for teams
Define and champion data modeling standards and best practices using tools like dbt
Boost data team productivity by improving tooling, automating workflows, and streamlining processes
Own decisions on tooling selection, balancing build vs. buy and managing vendor relationships when necessary
Partner closely with Data Scientists to ensure analytics requirements are clearly understood and effectively implemented
Develop and maintain critical dashboards and reporting to track business health and enable better decision-making
Lead data governance efforts, ensuring security, compliance, and quality standards are consistently met
Qualifications
Have 6-8+ years of professional experience as an analytics engineer, data engineer, data scientist, or closely related role
SQL expert
Experience in data modeling, including dimensional modeling and analytics engineering best practices
Experience creating high-impact dashboards and visualizations using BI tools (e.g., Omni, Mode, Hex, Looker, or similar)
Have prior experience in fast-paced, rapidly scaling environments
Comfortable working autonomously, taking projects from concept through execution with minimal oversight.
Bonus
Experience with dbt
Comfortable with Python
Experience with Snowflake administration and optimization
Familiarity or experience with Databricks
Previous experience as an early or first analytics engineer in a high-growth startup
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