Data Engineer, People Innovation Labs

About the Role

The role is part of the People Innovation Labs team, which is focused on rethinking how OpenAI finds and retains the best talent and empowers everyone to do their best work. From recruiting to culture, the team is designing systems that give the People Team a significant edge by infusing OpenAI's models and first-principles thinking into every aspect of their work.

What You Will Do

• Design, build, and manage people data pipelines, ensuring all data is seamlessly integrated into the 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 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
• Collaborate with cross-functional teams to identify and prioritize data needs and develop solutions
• Develop and maintain technical documentation for data systems and pipelines
• Participate in on-call rotations to ensure 24/7 support for data systems

What We Are Looking For

• 3+ years of experience as a data engineer and 8+ years of 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)
• Strong understanding of data modeling, data governance, and data quality
• Experience working with cross-functional teams, including data scientists, product managers, and engineers
• Strong communication and collaboration skills
• Experience with cloud-based data platforms, such as AWS or GCP
• Familiarity with data security and compliance frameworks, such as GDPR and HIPAA

Nice to Have

• Experience with machine learning and AI technologies, such as TensorFlow or PyTorch
• Familiarity with containerization technologies, such as Docker or Kubernetes
• Experience with agile development methodologies, such as Scrum or Kanban
• Familiarity with data visualization tools, such as Tableau or Power BI

Benefits and Perks

• Competitive salary and equity package
• Comprehensive health, dental, and vision insurance
• 401(k) matching program
• Flexible PTO and holiday schedule
• Remote work options and stipend
• Professional development opportunities and conference sponsorships
• Access to cutting-edge technologies and tools
• Collaborative and dynamic work environment
• Opportunity to work with a talented and experienced team
• Recognition and reward programs for outstanding performance

• To stand out as a candidate, highlight your experience with data engineering tools and technologies, such as Databricks, Snowflake, and Spark.
• Be prepared to discuss your approach to data modeling, data governance, and data quality, and how you have applied these principles in previous roles.
• Familiarize yourself with OpenAI's products and services, and be prepared to discuss how you can contribute to the company's mission and goals.
• Showcase your ability to work collaboratively with cross-functional teams, including data scientists, product managers, and engineers.
• Consider creating a portfolio or repository of your data engineering projects, and be prepared to walk the interviewer through your design and implementation decisions.
• Don't be afraid to ask questions about the company culture, team dynamics, and opportunities for growth and development.
• Be prepared to discuss your experience with cloud-based data platforms, data security, and compliance frameworks.