Member of Technical Staff (Software Engineer, Data Flywheel)

Pantera Capital; San Francisco (CA); Hybrid; USD 210,000 - 385,000; Full time

Job summary

A leading technology investment firm in San Francisco is seeking an experienced Data Engineer to build systems that enable various teams to access data efficiently. The candidate should have over 3 years of experience in software engineering, strong skills in Python and SQL, and familiarity with big data systems and AWS. The position offers a compensation range of $210K to $385K based on skills and experience, along with a hybrid work model and a comprehensive benefits package.

Qualifications

• 3+ years of software engineering experience shipping production systems.
• Strong proficiency in Python and SQL with production-grade code writing skills.
• Experience with big data systems including distributed compute and storage.

Responsibilities

• Build systems and pipelines enabling independent access to eval verdicts.
• Own the 'evals-to-product' loop for turning signals into datasets.
• Build a robust simulator pipeline for user interaction replay.
• Implement monitoring and quality checks to maintain data trust.
• Shape how the company measures and improves Answer Quality.

Skills

Python

SQL

Big Data Systems

Data Modeling

System Design

Debugging distributed systems

AWS

Databricks

AI-assisted development tools

Job description

Location

London, New York City, Belgrade

Employment Type

Full time

Location Type

Hybrid

Department

Data Science

Compensation

• $210K – $385K • Offers Equity

U.S. Benefits

Full-time U.S. employees enjoy a comprehensive benefits program including equity, health, dental, vision, retirement, fitness, commuter and dependent care accounts, and more.

International Benefits

Full-time employees outside the U.S. enjoy a comprehensive benefits program tailored to their region of residence.

USD salary ranges apply only to U.S.-based positions. International salaries are set based on the local market. Final offer amounts are determined by multiple factors, including experience and expertise, and may vary from the amounts listed above.

Perplexity serves tens of millions of users daily with reliable, high-quality answers grounded in an LLM-first search engine and specialized data sources. The Answer Quality team ensures that our prompts, tools, search, and specialized datasets, combined with both frontier and in-house models, create the best possible experience for our users. As our product evolves, our evaluations must remain fast, accurate, and actionable. In this role, you will build the data flywheel that serves teams across Perplexity.

Responsibilities

• Build the systems and pipelines that enable Search, Product, and other teams to independently access and utilize reliable eval verdicts without bottlenecks
• Take ownership of the "evals-to-product" loop, autonomously determining the best way to turn raw signals into durable datasets that power decision-making across the company
• Build a robust simulator pipeline capable of replaying user interactions with the product in formats legible to LLMs and VLMs, reflecting product changes as they are shipped
• Maintain data trust by implementing monitoring, lineage, and quality checks, ensuring downstream consumers can rely on the results implicitly
• Operate in a small, high-impact team where your work directly shapes how Perplexity measures and improves Answer Quality

Qualifications

• 3+ years of software engineering experience shipping production systems
• Strong proficiency in Python and SQL with the ability to write production-grade, maintainable code
• Experience with big data systems including distributed compute and large-scale storage
• Solid fundamentals in data modeling, system design, and debugging distributed systems
• Experience with AWS and lakehouse ecosystems like Databricks or Spark
• Comfortable with agentic coding workflows and using AI-assisted development tools to iterate faster

Preferred Qualifications

• Data engineering background including pipelines, orchestration, and warehousing patterns
• Familiarity with LLM/VLM interfaces, tokenization, structured formats, and multimodal payloads
• Experience with evaluation platforms, experimentation systems, or machine learning infrastructure
• Prior work supporting customer-facing products at scale

Compensation Range: $210K - $385K