Description
Compensation
$293K – $325K • Offers Equity
The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.
- Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
- Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
- 401(k) retirement plan with employer match
- Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)
- Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
- 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
- Mental health and wellness support
- Employer-paid basic life and disability coverage
- Annual learning and development stipend to fuel your professional growth
- Daily meals in our offices, and meal delivery credits as eligible
- Relocation support for eligible employees
- Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.
About the team
The Finance Data team is embedded within the CFO Org and is responsible for building internal data products that scale analytics across business teams and drive efficiencies in our daily operations. This team provides technical guidance on high-impact, scalable projects across Finance, and is the subject-matter expert in financial and transactional data that supports our Finance day-to-day operations.
About the Role
The Finance Data team is embedded within the OpenAI CFO Org (not under Engineering nor Product) and our team's mandate is ambitious yet simple:
1) The CFO Org has the data required to be Public Company Ready.
2) The CFO Org has all the data it needs to execute swiftly on our AI first roadmap.
3) Controllership is able to close the books without any manual spreadsheets in the shortest timeframe and with zero material risks.
As an Data Engineer on the Finance Data team, you will be setting the foundation to scale analytics across our business functions and impart best data practices for a rapidly growing organization. We aspire to build the Finance team of the future.
In addition, you will work collaboratively with key stakeholders in Finance and other business teams to understand their pain points and take the lead in proposing viable, future-proof solutions to resolve them. You will also autonomously lead your own projects that deliver business impact and help cultivate a mature data culture among Finance teams.
You might thrive in this role if you:
- 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 distributed processing technologies and frameworks, such as Hadoop, Flink 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.
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.
Required Skills
- Data engineering
- Distributed processing technologies and frameworks
- ETL schedulers
- Spark
Preferred Skills
- Programming languages (Python, Scala, Java)
- Cloud platforms (AWS, GCP, Azure)