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OpenAI
Analytics Data Engineer, Applied Engineering
atĀ OpenAI
about 2 months ago | 145 views | Be the first one to apply

Analytics Data Engineer, Applied Engineering

Full-time
San Francisco

About the company

OpenAIā€™s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. Our Communications team is composed of PR/Media Relations, Events, Design, and other external-facing functions. The teamā€™s ethos is to support OpenAI's mission and goals by clearly and authentically explaining our technology, values, and approach to safely building powerful AI. The Events team is a dynamic group dedicated to crafting extraordinary experiences that encompass our company's values and mission. Our team is driven by a passion for bringing people together to connect in meaningful ways.

Job Summary

In this role, you will:

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

You might thrive in this role if you:

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

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