Perplexity AI

Member of Technical Staff (Software Engineer, Data Platform)

San Francisco · Staff+

Sponsorship not specifiedDetected 48 days ago

TypeScriptPythonGoSnowflakeDatabricksKafkaMachine LearningSparkAirflowdbtData EngineeringData ScienceA/B Testing

About the role

The Data Platform team owns the end-to-end data lifecycle at Perplexity, from ingestion through processing, storage, and serving, powering product features, analytics, experimentation, AI workloads, and the company's data lake.
The team defines the architecture for batch and streaming systems, the orchestration and observability stack, and a self-serve data platform, while thoughtfully combining platforms such as Databricks and Snowflake with open-source technologies including Spark, Kafka, Flink, Airflow, Dagster, dbt, Iceberg, Delta Lake, and ClickHouse.

Design and operate large-scale batch and streaming data pipelines that directly power Perplexity product features, AI training and evaluation workflows, analytics, and experimentation.
Build event-driven and streaming systems (Kafka, Kinesis, PubSub, or similar) for real-time ingestion, transformation, and delivery, alongside batch frameworks for backfills, aggregations, and offline computation.
Lead the architecture of data orchestration using tools like Airflow or Dagster, owning scheduling, dependency management, retries, SLAs, and end-to-end observability for critical data flows.
Build self-serve data platforms that let engineers, data scientists, and analysts safely discover data, define contracts, and create and operate their own pipelines with minimal friction.
Drive architectural decisions across storage, compute, orchestration, and data APIs, partnering closely with product engineering and data science to align the data ecosystem with Perplexity's roadmap.
Mentor engineers, review designs, and raise the technical bar for data infrastructure through thoughtful feedback, documentation, and hands-on collaboration.
In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity's data ecosystem.

5+ years (Senior) or 8+ years (Staff) of software engineering experience.
Hands-on experience with batch and/or streaming data processing at scale.
Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.).
Experience supporting ML/AI workflows, training pipelines, or evaluation systems.
Familiarity with data quality, lineage, observability, and governance tooling.
Strong experience building production data infrastructure systems.
Deep familiarity with data orchestration systems (Airflow, Dagster, or similar).
Strong systems thinking around reliability, latency, cost, and complexity tradeoffs.
Prior ownership of internal platforms used by many teams.
If you're excited about this role, we encourage you to apply even if your experience doesn't match every qualification listed above.

This listing is sourced directly from Perplexity AI's careers page and normalized into a canonical job model.