Analytics Engineer, Real Estate and Workplace

OpenAI • San Francisco, CA

8d

About The Position

As an Analytics Engineer on the REW Data & Technology team, you will build high‑quality data models, pipelines, and Tableau assets that enable OpenAI to make data‑driven decisions about offices, workplace operations, and employee experience. You will work closely with Workplace Operations, Finance, and Technology teams to translate real‑world operational problems into reliable, scalable analytics products.
This role is focused on strong execution and delivery: shipping trusted datasets, building production dashboards, and contributing to a growing analytics platform that supports both human and agent-driven workflows.

Requirements

• 6+ years of experience in analytics engineering, data engineering, or analytics.
• Strong SQL skills and experience working with cloud data platforms.
• Comfort working with messy, operational, and real‑world datasets such as environmental sensor data, IoT data, or other event-based data sources.
• Experience with tools such as dbt, Airflow, or Spark, and real-time systems such as Kafka, Kinesis, Delta Live Tables, or Spark Structured Streaming.
• The ability to thrive in a fast‑moving, ambiguous environment where priorities can shift quickly.

Responsibilities

• Build and maintain business‑facing data models in Databricks and SQL that power REW reporting and planning.
• Develop and manage data pipelines for Tableau dashboards used by site leaders, operators, and executives.
• Define and maintain canonical REW metrics and documentation to ensure consistent decision-making across teams.
• Integrate data from HR systems, OfficeSpace, badge and access systems, meeting‑room bookings, and real-time presence and occupancy sensors.
• Implement data quality checks, tests, and monitoring to ensure the reliability of REW metrics.
• Build real‑time data pipelines that support agent-based operational applications.
• Partner with product managers and engineers to evolve and scale the REW data platform.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed