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# Software Engineer II

- **Company:** Uber
- **Location:** Sunnyvale, CA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $171,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Java (Programming Language), Application Programming Interfaces (APIs), Code Review, Shard (Database Architecture), Software Debugging, Fault Tolerance, Apache Hive, Python (Programming Language), Software Construction, Software Engineering, Web Applications, Jupyter Notebook, Apache Spark, Caching, Backend, Pandas, Pyspark, Information Technology, Production Code, Data Pipelines
- **Published:** October 22, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0ae0cbdd958cd593

## About the Role

* Bachelor's or Master's degree in Computer Science or a related technical field, or equivalent experience in an engineering related bootcamp
 * 2+ years of experience in professional software development experience, developing and deploying systems in production environments
 * Proven skills writing efficient, clean code in Go, Java, or Python
 * Ability to debug and fix software bugs in a production scale environment
 * Experience with software engineering best practices
 * Strong grasp of distributed-systems fundamentals: caching, sharding, consensus, fault tolerance, observability, and incident response
 * Excellent written and verbal communication skills, including the ability to document architectures and algorithms, * Advanced coursework or industry background in statistics, causal inference, or experimental design.
 * Direct ownership of analysis workflows (A/B, quasi-experimental, marketplace simulations) at scale.
 + Python, Pandas, PySpark
 + Data Pipelines (e.g. Spark, Scala)
 + Jupyter Notebooks
 * Fullstack development experience (BE, FE, Data Pipelines), this project involves a full suite of development surfaces across UI, backend, and data.
 * Experience developing internal tooling used by Ops, Engineers, Finance, Scientists, etc.

## Description

* Build and own data pipelines (Spark, Hive, scheduled workflows) that recompute lever-efficiency estimates from experiment and marketplace data every week. Include data-quality checks, freshness alerts and backfills.
 * Build backend services and APIs in Go that store and serve efficiency estimates and budget recommendations.
 * Ship full-stack features in the web app: interactive dashboards and a budget allocation tool used by Operations, Finance, Product, and Science.
 * Work with data scientists to turn notebook prototypes into production code. This includes confidence intervals, corrections for network effects, forecasts, and an optimizer that moves budget between levers within real constraints, such as fixed total spend and capped weekly changes.
 * Work with Uber's experimentation platform to run experiments that test budget moves (switchbacks, geo experiments, synthetic control), and automate reading their results into the dashboard.
 * Take features from design to launch: write design docs, review code, test, monitor production, and take part in on-call. Document methodology and system design so partners can trust and reuse the numbers.
*