About the Role

Data underpins our products, enabling intelligent decision-making, and improved user experiences. Leveraging the state-of-the-art data processing technologies, the Global Data Warehouse team builds and maintains high-quality, analytics-optimized canonical data models derived from petabytes of raw data and deliver actionable insights through various reporting methods.

As a Software Engineer - Data, you will play a leading role in scaling the core data warehouse to power analytics for teams across Uber. You are a self-starter with demonstrable experience leveraging Hadoop, Spark, and Presto at scale when building data solutions. Peers describe you as the go-to person for the most challenging data architecture, ingestion, processing, and data modeling problems. You are able to balance multiple simultaneous projects. You regularly perform code reviews and help define code quality standards for your team. Detail-oriented thoroughly tested code, high data integrity, and great documentation are the hallmarks of your work but you excel equally well at explaining concepts in "big picture" terms to a less technical audience. If this describes you and you tick off the boxes below, we would love to hear from you.

What the Candidate Will Do:

• Software Engineers in GDW focus on data architecture, design, source data instrumentation, ETL pipeline optimization, and data model implementation.
• Collaborate with HDFS, Hive, Presto, and Spark teams to build efficient and scalable solutions for end-users.
• Contribute on ETL tooling framework to implement and extend its functionality using Python such that all users of the framework benefit from it.
• Identify limitations and required features in Data tools and partner with peer teams to design and implement them.
• Automate manual work by developing scripts and utilities for repeated tasks.
• Own big data problems, understand all underlying infra systems and platforms, and work towards improving resource requirements and customer SLA.

Basic Qualifications:

• BS or MS in Computer Science or a related technical field, or equivalent experience.
• Expertise in creating and evolving dimensional data models & schema designs to structure data for business-relevant analytics.
• Hands-on experience in SQL or Spark to build and deploy production-quality ETL pipelines.
• Experience writing and deploying code in one of the following programming languages: Python, Scala, or Java.
• Atleast 4 years of experience

Preferred Qualifications:

• Experience building high-quality end-to-end data solutions that scale to meet future needs using big data technologies like Hadoop, Hive, and Spark.
• Ability to raise the bar for other engineers by proposing and driving innovative ideas, passionate about bringing efficiency into the system through optimizations.
• Familiarity with Kimball's data warehouse lifecycle.
• Experience with real-time data ingestion and stream processing.
• Track record of partnering with product and engineering teams to deliver data products.
• Experience developing utilities and tools to enable faster data consumption.

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 10,000 cities around the world.

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.

Uber is proud to be an Equal Opportunity/Affirmative Action 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.