Senior Cloud Engineer - Efficiency Engineering
Uber
About the Team
We are hiring a Cloud Engineer within the Cloud Engineering & Tech Strategy (CETS) Team at Uber. The CETS team ensures a resilient and scalable tech foundation that supports Uber’s efficient growth and innovation. We drive tech strategy, cloud migration, data center management, and capacity engineering, while ensuring sustainable growth.
Within the CETS organization this role supports the Cloud Capacity Operations, Reliability, and Engineering (C.O.R.E) Team focused on infrastructure efficiency, end-to-end capacity management, quota governance, capacity forecasting, multi-region cloud strategy, and cloud migration.
About the Role
As a Senior Cloud Engineer within the Cloud C.O.R.E team you will be a key driver of technical optimization and financial accountability across our cloud environments. You will play a critical role in cloud consumption data analysis, forecasting, and the identification and execution of engineering and financial optimizations. You will leverage your expertise in cloud engineering, data analysis, and machine learning to optimize our infrastructure, improve our forecasts, and deliver efficient growth for Uber.
What you will do
1. Identify and spearhead optimization opportunities through analysis of cloud consumption data.
2. Partner with Compute, Data, and Storage engineering teams to identify, prioritize, and implement platform efficiencies.
3. Establish key cloud efficiency metrics and partner with engineering to implement efficiency and price-performance optimizations within Uber’s production scaling systems.
4. Define and manage reporting of cloud consumption metrics and KPIs, ensuring transparency, accuracy, and accountability.
5. Exercise excellent judgment on engineering/business trade-offs across cloud optimization opportunities (build vs. buy vs. rewrite, velocity vs. efficiency vs. critical features, etc.).
6. Support commitment strategies, ensuring commitment decisions that optimize spend and best serve the business and technical strategy.
7. Embed cloud consumption shift-left principles into engineering design and architecture.
8. Act as a bridge between engineering and leadership on key drivers of consumption trends, biggest areas of opportunities, risks, and impact of optimization efforts.
9. Collaborate on infrastructure demand planning across key infrastructure growth metrics.
10. Partner with engineering to improve consumption and efficiency reporting across internal tooling.
11. When faced with an ambiguous situation, difficult problems, or differing opinions, you’ll establish the facts and use a structured approach to drive the discussion and bring partner teams to a shared understanding.
---- Basic Qualifications ----
- M.S. or B.S. degree in Computer Science, Engineering, Economics, Statistics, Machine Learning, Operations Research, or other quantitative fields.
- 5+ years of industry experience working with Cloud, either at a hyperscaler, as an integrator, or within the engineering organization of a cloud customer.
- Familiarity with cloud compute, storage, and data technologies, demonstrated through either multiple years of experience on a team building cloud products, or managing the consumption of numerous cloud products, or through accreditation from numerous cloud certifications (in addition to on the job experience).
- Excellent communication and collaboration skills: Able to lead initiatives across multiple areas and communicate findings with leadership and engineering teams.
- Experience in leading key technical projects and substantially influencing the scope and output of others.
- Fluency in MS Excel/Google Sheets for analysis and collaboration.
---- Preferred Qualifications ----
- Background in at least one programming language (eg. Python, R, Java, Ruby, Scala/Spark or Perl).
- Experience with cost optimization analysis & implementation, ideally for cloud spend or compute infrastructure.
- Experience in contributing to performance optimization initiatives through experimentation.
- Experience with exploratory data analysis, statistical analysis, and model development.
- Ability to use Python or similar technologies to work efficiently with large data sets and prototype algorithms & models.
- Coding and SQL proficiency and ability to develop statistical analysis and algorithm prototyping in Python or R.
For San Francisco, CA-based roles: The base salary range for this role is USD$180,000 per year - USD$200,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD$180,000 per year - USD$200,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD$180,000 per year - USD$200,000 per year.
For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.
Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.
Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.