Data Engineer
Magnite
- New York, New York, United States
- New York, New York, United States
Über
More than anything we expect you to love learning and see problems as things to overcome rather than blockers
You should look at this list and our tech stack and think “wow i want to learn that”, rather than being an expert
We expect you to have expertise with 1-2 items and familiarity with a couple more. Most candidates will have 2+ years of experience
Hands‑on experience with Apache Spark (mainly PySpark). Ideally, you will have written a variety of pipelines that you have deployed in production
Strong Python skills, particularly in the context of Databricks and Spark
Data pipeline design knowledge, from sourcing event data to creating queryable data layers
Familiarity with event‑based data architecture (e.g., Kafka)
SQL experience for data analysis and transformations
Hands‑on experience with AWS and Terraform for IaaS solutions
Experience writing Jenkins or GitHub actions pipelines to run build and integration actions
GoLang for distributed service development
Kubernetes experience
What the job involves
You will join the Innovative Services Group (part of the wider Audience team). Innovative services build solutions across the Audience group (and beyond) that are leveraged by other teams
Examples include probabilistic services able to handle over 500k requests a second, and optimising how compute is deployed in our data pipelines yielding very high cost savings across the teams
The wider Audience team is responsible for managing and delivering the first and third‑party data that powers all of the platforms that Magnite operates
We’re a globally distributed team of software and data engineers who build and operate huge scale data pipelines and real‑time scaled services to enable Magnite and Magnite’s customers to reach their goals
This role is focused on the data engineering side of the team’s responsibilities, and this job listing reflects that, but there is an opportunity to get involved more broadly
Build and optimize data pipelines using Apache Spark and Python, processing billions of events in both streaming and batch modes. We work at TB scale
Collaborate with senior data engineers to improve Magnite’s Audience data pipelines by identifying and implementing innovative solutions
Own the operational performance of your builds, ensuring uptime and implementing recovery strategies
Collaborate with SRE teams to provision infrastructure using Terraform and AWS (future Kubernetes on‑premise)
Proactively identify and help solve impactful problems
You are part of a team that moves fast, makes incremental improvements towards a vision and solves problems other teams are struggling with
Note: given the seniority of this position, we don't expect you to be here on day one, but this is what you can expect to grow into
Our current tech stack:
Python, Golang, Rust, Java / Spring Boot
ECS, Fargate, Kubernetes
Spark, Databricks
Luigi, Airflow
Docker
ALB, HAProxy
RDS, MariaDB, Postgres
Redis, Memcache
Kafka, SNS, SQS
Terraform, GitHub Actions, Jenkins
JavaScript / TypeScript / React
Linux (both on‑premise and AWS)
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Sprachkenntnisse
- English
Hinweis für Nutzer
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