Senior Data Engineer, Core Experimentation

OpenAI•Seattle, WA

4d•Hybrid

About The Position

The Statsig team at OpenAI builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI!

Requirements

3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering).
Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.
Experience with distributed processing technologies and frameworks, such as Hadoop, Flink and distributed storage systems (e.g., HDFS, S3).
Expertise with any of ETL schedulers such as Airflow, Dagster, Prefect or similar frameworks.
Solid understanding of Spark and ability to write, debug and optimize Spark code.

Responsibilities

Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse.
Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.
Work collaboratively with various teams, including, Infrastructure, Data Science, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions.
Implement robust and fault-tolerant systems for data ingestion and processing.
Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear.
Ensure the security, integrity, and compliance of data according to industry and company standards.