Data Engineer, Real Estate and Workplace

7 days ago

San Francisco, California, United States OpenAI Full time

About the Team

At OpenAI, our Real Estate and Workplace team is responsible for planning our Real Estate needs and elevating the employee experience through different delineations of the industry (Facilities, Operations, Experience) to support our growing company in its mission to ensure that AGI benefits all of humanity.

We're looking for individuals who are enthusiastic about using technology to understand and improve the employee experience of an organization with a mission.

This role is based in San Francisco, CA, and we offer a hybrid work model of 3 days in the office per week and relocation assistance to new employees.

About the Role

As an early member of our Real Estate and Workplace data team, you will be instrumental in designing and implementing the core of our data architecture and pipeline, enabling us to scale our analytics and uncover innovative solutions for our rapidly maturing organization.

You will autonomously lead your own projects to enable consumption from various data sources to help steer real estate and workplace teams to make data-driven decisions on planning and operations.

You'll also guide the strategic planning, management, and optimization of data and technological infrastructure to support workplace and real estate analytics and operations.

Over time, you will have the growth opportunity to call a functional domain your own and be responsible for maintaining a service end-to-end.

Responsibilities

  • Design, build, and manage our data pipelines, ensuring all internal real estate and service-related activity data, including location-based and IoT sensor data, is seamlessly integrated into our data warehouse.
  • Create scalable pipelines for data collection, cleaning, and analysis from multiple sources, and manage the lifecycle of metrics and models from prototyping to production.
  • Implement robust and fault-tolerant systems for data ingestion and processing, allowing timely consumption of data.
  • Work collaboratively with various teams, including IT, Data Engineering, Data Platform, Finance data, and HR to enable successful data ETL and build systems that utilize workplace data.
  • Collaborate to understand the data needs of various stakeholders in Real Estate Planning, Workplace Operations, HR, and Finance.
  • 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.

Requirements

  • 5+ years of experience performing data engineering roles, with experience of owning an end-to-end data pipeline.
  • Proficiency in at least one programming language commonly used within Data Engineering, preferably Python and SQL.
  • Experience processing high-volume data with distributed processing technologies and frameworks, such as Hadoop, Kafka, 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.
  • You are comfortable dealing with a wide variety of data including unstructured data and high-volume real-time sensor data.
  • You have experience processing organizational activity data and/or spatial sensor data preferably in an enterprise setting.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.

We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products.

AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or any other legally protected status.

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