The Hadoop Platform team aims to build the next generation of intelligent data services that will profoundly impact how we march towards the vision of Uber's data-driven, real-time marketplace. Our team builds libraries and distributed services around the Hadoop stack (Hive, Presto, HDFS, Kafka, ....) to ease user interaction with the Big Data world. We share them with the open-source community (e.g., Hudi or Marmaray).
The Data Ingestion team owns the platform that moves hundreds of TBs of data a day from thousands of data sources to Uber's data lake. The hundreds of PBs data ingested by the Data Ingestion platform is the source of truth for business analytics and insights at Uber, powering various data-driven decisions. The platform consists of Marmaray, built from the ground-up at Uber and various services and tooling to operate the Data ingestion platform at scale and to deliver new data to customers at lower latencies.
What you will do:
We are currently looking for a strong engineer to join the Data Ingestion team to

1. Design and implement distributed solutions to make new data available faster for business analytical needs.
2. Drive reliability and operational scalability improvements through design and automation - scaling with the ever-increasing data volume flowing through the systems and the number of data sources producing data, observability, and monitoring.
3. Drive efficiency efforts for one of the largest consumers of Uber's Data Infrastructure.
4. Collaborate with multiple partner teams to achieve these multi-faceted goals.

Basic Qualifications ----

1. Bachelor's degree with 4+ years of experience.
2. Strong problem solving and coding skills in at least one of Java / C++ / Python.
3. Experience with developing, debugging, and shipping software products on large codebases.

Preferred Qualifications ----

1. Masters or Ph.D. in Computer Science or related subject area.
2. Experience designing and executing large-scale distributed applications.
3. Experience with big data infrastructure tools and software such as Spark, HDFS, Yarn.
4. Demonstrated experience working collaboratively in cross-functional teams.
5. Passion for learning new technologies, domains, and challenging the status quo.