About the job:
Uber critically depends on search, routing, and navigation services to power its business. The world’s road systems, addresses, and places are always changing and consequently these services need to operate on the latest and most accurate map. As the Engineering Manager in the Map Data organization you will lead a group of engineers building solutions so that changes to the map are continuously ingested, enriched, edited, verified and deployed to these services all the while serving hundreds of thousands of concurrent trips by drivers and couriers all around the globe!
- Deliver business impact by working with partners to come up with success metrics and execute on concrete action plans.
- Understand the architecture of your team’s services and pipelines as well as any that are dependent. Your prior experience will allow you to provide input and guidance on the design of new components where needed.
- Establish the team vision and roadmap by assessing the direction of the company and the needs of customer teams. You will align and translate this into short team tactical plans and a longer-term vision.
- Hire and develop engineering talent
- Collaborate and influence other business partners by sharing and communicating roadmaps with external teams &setting shared goals across teams to collectively deliver results efficiently.
- Experience working with product managers and infrastructure teams to identify, prioritize, and solve problems
- 2+ years of experience managing teams of 6 or more engineers across all levels.
- A computer science, or engineering undergraduate degree or equivalent experience, including hands-on software development experience.
- 4+ years of experience managing teams of 8 or more engineers across all levels.
- Track record of leading, recruiting, and retaining strong engineering talent and growing effective teams.
- Experience with large-scale, distributed systems, including SQL/NoSQL storage, transactional updates, asynchronous processing with message queues like Kafka, logging, system monitoring, and performance tuning.
- Experience with large-scale data storage and processing pipelines with technologies like Spark, Hive, HBase, etc.
- Experience working with multi-functional, globally distributed teams to coordinate work and deliver solutions that span multiple teams.