Software Engineer, Data Platform

Persona•San Francisco, CA

1d•$130,000 - $220,000

About The Position

Persona is the configurable identity platform built for businesses in a digital-first world. Verifying individuals and organizations is harder — but more important — than ever, with AI enabling fraudsters to launch sophisticated accounts at scale and regulations evolving rapidly. We’ve built Persona to support practically every use case and industry — that’s why we’re able to serve a wide range of leading companies. We’re growing rapidly and looking for exceptional people to join us! We are looking for passionate engineers who are excited to build the data foundation for the identity layer of the internet. As an engineer on the Data Platform team at Persona, you'll design, build, and operate the systems that move and store data at massive scale — a datalake, the streaming and batch pipelines that feed it, a multi-provider warehouse layer, and the services built on top of it all. You'll work the full depth of that stack, from raw ingestion through storage layout and compute all the way to the query layer — owning the performance, reliability, and cost of each. This is a high-ownership role on a small team, working closely with the rest of engineering, data science, and infrastructure to make the platform fast, reliable, and cost-efficient at hundreds of billions of records per day.

Requirements

3+ years of experience in software engineering, with a focus on data infrastructure or large-scale distributed systems.
Proficiency in Python — our primary language across pipelines. Our newest services are written in Go, so you either work in Go today or are excited to ramp into it.
Hands-on experience with big-data or streaming technologies such as Spark, Kafka, or Flink, and interest in lakehouse table formats like Iceberg.
Experience building and operating scalable data pipelines across structured and unstructured data.
Strong fundamentals in distributed systems, storage, and performance/cost optimization.
Excellent communication and collaboration skills across engineering, data science, and infrastructure teams.

Nice To Haves

ClickHouse, DuckDB, Google Cloud (GCP), Kubernetes, MySQL, MongoDB, Snowflake.

Responsibilities

Build and scale our datalake — the pipelines that feed it and the storage design that keeps it fast and efficient.
Develop high-throughput data-movement and ingestion services that bring data into the platform reliably and at scale.
Own streaming and batch ingestion and the change-data-capture pipelines that absorb billions of records and terabytes of data per day.
Build new query and analytics capabilities directly on the datalake — for use cases that don't fit a traditional warehouse.
Operate the low-latency serving layer for real-time, high-concurrency access to platform data.
Partner with infrastructure and product teams to provision, secure, and scale the platform.