How can Uber plan pricing and incentives to meet financial goals while keeping its marketplace healthy and growing? That’s the challenge our Mobility Simulation and Planning (MSP) organization tackles within Marketplace.
MSP builds forecasting, simulation, and optimization products that help Operations teams translate financial targets into pricing and incentive policies across hundreds of cities. Our planning product, Planner, brings these capabilities together to generate actionable price plans. Supporting this work requires dependable data, scalable model training and simulation, and reliable workflows for generating and deploying plans.
The MSP Infra team builds the data and computing foundations that make these capabilities possible. We partner with engineers and scientists to turn complex data and modeling workflows into reliable, scalable, reusable infrastructure.
We’re looking for a Senior Software Engineer with a strong infrastructure background and a focus on data-intensive systems. You’ll build and evolve feature stores, distributed data pipelines, and self-service tooling that support forecasting, simulation, optimization, and financial measurement. Your work will help teams move from new data and modeling ideas to dependable production workflows.
The challenges go beyond moving data from one place to another. How do we keep model inputs fresh and consistent as upstream sources evolve? How do we efficiently rebuild historical features for simulation and backtesting? How do we make complex data operations safe and self-service? You’ll solve these problems through hands-on engineering, cross-team collaboration, and end-to-end ownership of production systems.
What you’ll do- Build scalable data infrastructure: Design and evolve shared feature stores and distributed processing pipelines that support model training, inference, backtesting, simulation, and planning.
- Make data trustworthy: Develop automated validation, monitoring, and alerting to detect freshness, completeness, and correctness issues before they affect downstream consumers.
- Improve data lifecycle operations: Build efficient capabilities for incremental processing, historical backfills, schema evolution, data versioning, and recovery from failed or incorrect writes.
- Enable self-service: Create reusable frameworks, APIs, and developer tooling that help engineers and scientists onboard features, investigate issues, and operate workflows with less manual support.
- Optimize performance and cost: Identify bottlenecks in data processing, storage, and orchestration, and improve throughput, resource efficiency, and reliability.
- Drive technical projects end to end: Translate ambiguous requirements into designs, lead implementation and rollout, and own production health through on-call, incident response, and long-term improvements.
- Collaborate and mentor: Partner with modeling, financial-data, and shared-platform teams to establish consistent data foundations; guide engineers through thoughtful design reviews, code reviews, and technical mentorship.
- 6+ years of professional experience in software engineering, data infrastructure, or a related technical role.
- Strong programming skills in Python, Java, Scala, Go, or a comparable language.
- Experience designing, building, and operating large-scale data pipelines or distributed data-processing systems.
- Strong SQL skills and experience with data modeling, storage systems, and query-performance optimization.
- Experience delivering technical projects from design through production rollout and ongoing operations.
- Ability to communicate technical tradeoffs and collaborate across engineering and data science teams.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience.
- Experience with Apache Spark or comparable distributed data-processing frameworks.
- Experience with Apache Hudi or similar data lake technologies supporting incremental updates, schema evolution, and versioned datasets.
- Experience building feature stores or data infrastructure for machine learning, forecasting, optimization, or simulation.
- Experience developing reusable data-quality frameworks, observability systems, or tools for tracing and reconciling data across sources.
- Familiarity with workflow orchestration and distributed computing frameworks such as Ray.
- Experience building self-service platforms or automation that reduces operational overhead for engineers and scientists.
- A track record of measurable improvements in data reliability, processing performance, infrastructure cost, or developer productivity.
Responsibilities
For New York City, NY-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For Seattle, WA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.
For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 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.
About UsReady to Ride?
This isn't the kind of place where you follow a playbook — it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves — we'd love to hear from you.
You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.
Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.
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.
Skills Required
- 6+ years of professional experience in software engineering, data infrastructure, or a related technical role
- Strong programming skills in Python, Java, Scala, Go, or a comparable language
- Experience designing, building, and operating large-scale data pipelines or distributed data-processing systems
- Strong SQL skills and experience with data modeling, storage systems, and query-performance optimization
- Experience delivering technical projects from design through production rollout and ongoing operations
- Ability to communicate technical tradeoffs and collaborate across engineering and data science teams
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience
- Experience with Apache Spark or comparable distributed data-processing frameworks
- Experience with Apache Hudi or similar data lake technologies supporting incremental updates, schema evolution, and versioned datasets
- Experience building feature stores or data infrastructure for machine learning, forecasting, optimization, or simulation
- Experience developing reusable data-quality frameworks, observability systems, or tools for tracing and reconciling data across sources
- Familiarity with workflow orchestration and distributed computing frameworks such as Ray
- Experience building self-service platforms or automation that reduces operational overhead for engineers and scientists
- Track record of measurable improvements in data reliability, processing performance, infrastructure cost, or developer productivity
Uber Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Uber and has not been reviewed or approved by Uber.
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Parental & Family Support — Policies provide a minimum of fully paid parental leave for all parents and financial support for fertility, adoption, and surrogacy, with added credits to ease the transition. Programs extend to family medical leave and parenting support resources, indicating depth beyond baseline offerings.
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Healthcare Strength — Healthcare coverage is described as comprehensive across many countries, with medical, dental, vision, life, disability, and mental health benefits, plus allowances where direct plans are not available. Wellness programs and reimbursements further reinforce access to care.
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Wellbeing & Lifestyle Benefits — Monthly ride and meal credits, free office meals/snacks, fitness stipends, onsite gyms, and wellbeing reimbursements create meaningful everyday value. Home‑office stipends, travel medical coverage, and counseling support round out lifestyle-oriented perks.
Uber Insights
What We Do
We are Uber. The go-getters. The kind of people who are relentless about our mission to help people go anywhere and get anything. Movement is what we do. It’s our lifeblood. It runs through our veins. It’s what gets us out of bed each morning. It pushes us to constantly reimagine how we can move better. For you. For all the places you want to go. For all the things you want to get. For all the ways you want to earn. Across the entire world. In real-time. At the incredible speed of now.
Why Work With Us
We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.
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