Staff Software Engineer - Data

Are you interested in building high-performance, globally scalable financial systems that support Uber's current and future growth? Are you constantly looking to invent newer and simpler ways of building solutions? Does the prospect of working with top engineering talent get you charged up? If so, Uber Finance Tech (FinTech) is for you!

The FinTech team at Uber builds technology solutions and services that enable Uber's new business growth through automation and self service, the monthly closing of books, quarterly wall street reporting, provides Billing (Invoices, Receipts) services to our earner partners and ensures regulatory compliance worldwide.

---- What the Candidate Will Do ----

1. Provide technical leadership in architecting, implementing, testing, releasing and monitoring data models for intuitive analytics and business insights
2. Build strong relationships with people in the organization, meaningfully collaborating and building trust
3. Actively seek out the engineering and business problems, solve them with little to no guidance.
4. Be a role model on acting with good judgement and responsibility. Engineers across the organization will look to you on how best to plan and execute on projects
5. See the big picture and identify strategically important problems, inefficiencies or opportunities for meaningful improvements. Drive alignment on how to tackle these and deliver high leverage solutions on these at the group and organization level
6. Raise the bar on sustainable engineering by improving best practices, producing best in class of code, documentation, testing, and monitoring rolling out the next generations of our fintech systems
7. Be a humble mentor and trusted advisor for both our talented team members and passionate leaders alike. Deal with a difference in opinions in a mature and fair way, helping teams to commit and move forward.

---- Basic Qualifications ----

1. Bachelor's or Master's degree in Computer Science or related field
2. Passion for driving continual improvement initiatives on engineering best practices like coding, testing or monitoring
3. Solid technical leadership abilities, and comfortable working with various stakeholders to ensure adoption/impact
4. Extensive experience designing and managing data pipelines, dimensional data models and data warehouses to structure data for business-relevant analytics
5. Experience working with end to end distributed data systems for logging, storage, ETL, data quality and monitoring
6. 10+ years of hands-on experience using SQL to build and deploy production-quality ETL pipelines
7. 10+ years of hands-on experience using Hadoop, Hive, Vertica or other MPP databases (AWS, Redshift, Terradata etc)
8. Experience developing scripts and tools to enable faster data consumption
9. Proven track record of results as a Staff Engineer level or above at a premier technology company
10. Excellent written and verbal communication skills, including the ability to write detailed technical documents
11. Passionate about helping teams grow by inspiring and mentoring engineers

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.

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.

*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.

Client-provided location(s): Hyderabad, India

Job ID: Uber-144859

Employment Type: FULL_TIME

Posted: 2025-08-14T00:28:05