Data Engineer, People Innovation Labs

OpenAI; San Francisco (CA); On-site; USD 293,000 - 325,000; Full time

Job summary

OpenAI is seeking a data engineer in San Francisco to design and manage data pipelines that support the People Innovation Labs. Candidates should have at least 3 years of data engineering experience and 8 years of software engineering. Proficiency in programming languages like Python or Java, along with experience in data warehousing technologies such as Databricks, is essential. The compensation range is $293K - $325K, positioning this role as a key part of OpenAI's mission-driven team.

Qualifications

• 3+ years of experience as a data engineer and 8+ years of software engineering.
• Proficiency in Python, Scala, or Java.
• Experience with data warehousing and ETL technologies.

Responsibilities

• Design, build and manage people data pipelines for integration.
• Develop datasets to track key metrics and product metrics.
• Collaborate with various teams to understand data needs.

Skills

Data engineering

Software engineering

Data pipeline management

Collaboration with teams

Data security and compliance

Tools

Databricks

Snowflake

ETL schedulers

Spark

Job description

About the Team

At OpenAI, we're building the connective tissue between our mission and our people. People Innovation Labs is a fast-moving engineering team embedded in the People organization, focused on rethinking how we find and retain the best talent and empower everyone to do their best work. From recruiting to culture, we're designing systems that give our People Team a significant edge by infusing OpenAI's models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We're defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation.

About the Role

We're seeking a data engineer to build data-intensive systems that power People Innovation Labs' internal products and enable the People Analytics function to do their best work. These data pipelines are crucial for our build-out of people products backed by business systems of record and for ongoing people data analytics. In this role, you will work with People Innovation Labs leadership and software engineers and the People Analytics team to build the data systems that enable this work.

In this role, you will:

• Design, build and manage people data pipelines, ensuring all data is seamlessly integrated into our Databricks warehouse.
• Develop canonical datasets to track key people metrics and People Innovation Labs product metrics.
• Work collaboratively with various teams, including Data Platform, Data Science, People Analytics, and Compensation and Equity 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 as the primary data engineering expert on the team.
• Ensure the security, integrity, and compliance of data according to industry and company standards.

Your background might look like:

• 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 data warehousing technologies such as Databricks and Snowflake, and expertise with ETL schedulers such as Fivetran, Airflow, Dagster, Prefect, or similar.
• Experience with distributed processing technologies and frameworks, such as Spark, Hadoop, Flink and distributed storage systems (e.g., HDFS, S3).

Compensation

Compensation Range: $293K - $325K

Equal Opportunity Employer

OpenAI is an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.