Marketing Data Engineer
@ OpenAI

San Francisco, CA
$330,000
On Site
Full Time
Posted 1 day ago

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XXXXXXXXX XXXXXXXXXXX XXXXXXX****** @openai.com
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Job Details

About The Team

Business Data Science & Analytics is OpenAI’s hub for applying data to growth, revenue, and go-to-market strategy. The team builds centralized data models powering decision-making across Marketing, Sales, Partnerships, and more.

About The Role

As a Marketing Data Engineer at OpenAI, you will build critical data pipelines and core marketing datasets to measure ROI, guide investments, and accelerate product adoption globally. You will partner with multiple teams to shape OpenAI’s growth strategy.

Key Responsibilities

  • Design, build, and manage marketing data pipelines.
  • Develop canonical datasets for key business metrics like spend, LTV, CAC, ROI.
  • Collaborate with Marketing, Partnerships, Data Science, Finance, and Product teams.
  • Implement robust data ingestion and processing systems.
  • Ensure data security, integrity, and compliance.

What You Bring

  • 3+ years as a Data Engineer and 8+ years in software engineering.
  • Proficiency in Python, Scala, or Java.
  • Experience with distributed processing and storage technologies like Hadoop, Flink, HDFS, and S3.
  • Skilled with ETL tools such as Airflow, Dagster, or Prefect.
  • Solid understanding of Spark and marketing data sources.

About OpenAI

OpenAI is an AI research company dedicated to ensuring that general-purpose AI benefits all of humanity. The company values diverse perspectives and strives to deploy AI safely for global benefit.

Key Skills/Competency

  • Data Pipelines
  • ETL
  • Spark
  • Python
  • Distributed Systems
  • Marketing Analytics
  • Data Security
  • Collaboration
  • Data Modeling
  • Compliance
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How to Get Hired at OpenAI

🎯 Tips for Getting Hired

  • Research OpenAI's culture: Study mission, values, and recent initiatives.
  • Customize your resume: Highlight relevant data engineering projects.
  • Showcase technical expertise: Emphasize ETL and Spark skills.
  • Prepare for interviews: Review case studies and system design.

📝 Interview Preparation Advice

Technical Preparation

Review ETL tool documentation.
Practice Spark code optimization.
Study distributed processing frameworks.
Brush up on Python programming.

Behavioral Questions

Describe a challenging team collaboration instance.
Explain your problem-solving process.
Discuss handling ambiguous project requirements.
Share experience managing competing priorities.

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