Member of Technical Staff (Software Engineer, Data Platform)

Описание

Perplexity is hiring a senior/staff data platform engineer to design and operate large-scale batch and streaming data systems. The role owns data orchestration, self-serve platform tooling, and reliability guarantees for product analytics, experimentation, and AI workloads. It involves Python and data infrastructure technologies such as Spark, Kafka, Airflow, and Dagster.

Responsibilities

• 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
• Set and enforce guarantees for data correctness, freshness, lineage, and recoverability, designing systems that handle rapid scale growth, partial failures, and evolving schemas without disrupting AI workloads or product experiences
• 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
• Improve developer experience through better abstractions, opinionated paved paths, and standards for data modeling, testing, validation, and deployment, treating the data platform as a product used by many teams
• 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

Requirements

• 5+ years (Senior) or 8+ years (Staff) of software engineering experience
• Strong experience building production data infrastructure systems
• Hands-on experience with batch and/or streaming data processing at scale
• Deep familiarity with data orchestration systems (Airflow, Dagster, or similar)
• Proficiency in Python and at least one additional backend language (Go, TypeScript, etc.)
• Strong systems thinking around reliability, latency, cost, and complexity tradeoffs
• Experience supporting ML/AI workflows, training pipelines, or evaluation systems
• Familiarity with data quality, lineage, observability, and governance tooling
• Prior ownership of internal platforms used by many teams