Analytics Data Engineer, Applied Engineering

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About the team
The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the role: 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! In this role, you will: 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, 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.
You might thrive in this role if you: Have 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.
This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees.
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Location:
San Francisco

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