Senior Data Platform Architect

Maven Ventures; Palo Alto (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Perplexity is seeking a senior/staff Data Platform Engineer to shape architecture and set standards for its data ecosystem. You will lead large-scale batch and streaming pipelines powering product features, analytics, and AI workloads, and drive end-to-end observability and data quality.

You will mentor engineers and collaborate with product engineering and data science to align with the roadmap. You will build self-serve data platforms, improve developer experience, and define contracts and

Qualifications

• 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.

Responsibilities

• Design and operate large-scale batch and streaming data pipelines powering product features, AI training and evaluation workflows, analytics, and experimentation.
• Build event-driven and streaming systems for real-time ingestion, transformation, and delivery, plus batch backfills and offline computation.
• Lead the architecture of data orchestration using Airflow or Dagster with end-to-end observability.
• Ensure data correctness, freshness, lineage, and recoverability amid rapid scale and evolving schemas.
• Build self-serve data platforms enabling engineers, data scientists, and analysts to discover data and create pipelines with minimal friction.
• Improve developer experience with abstractions, paved paths, and standards for data modeling, testing, validation, and deployment.
• Drive architectural decisions across storage, compute, orchestration, and data APIs in alignment with roadmap.
• Mentor engineers, review designs, and raise the technical bar with documentation and collaboration.

Skills

Python

Go/TypeScript

Batch processing

Streaming data

Data orchestration

Observability

Mentoring

ML/AI workflows

Tools

Airflow

Dagster

Kafka

Kinesis

PubSub

Spark

Iceberg

Delta Lake

Job description

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.

In this senior/staff role, you will shape architecture, set standards, and drive the long-term technical direction of Perplexity’s data ecosystem.

Key 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.

Qualifications

• 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.