This list contains only the countries for which job offers have been published in the selected language (e.g., in the French version, only job offers written in French are displayed, and in the English version, only those in English).
As an Engineer on the Data Intelligence team, you will be dealing with large scale data pipelines and data sets that are critical and foundational for Uber to make decisions for better customer experience. You will be working on a petabyte scale of analytics data from the multiple Uber applications. Help us build the software systems and data models that will enable data scientists to understand our user behavior better and thrive on the data driven mindset at Uber.
Job Responsibility:
Responsible for defining the Source of Truth (SOT), Dataset designfor multiple Uber teams
Identify unified data models collaborating with Data Science teams
Streamline data processing of the original event sources and consolidate them in source of truth event logs
Build and maintain real-time/batch data pipelines that can consolidate and clean up usage analytics
Build systems that monitor data losses from the different sources and improve the data quality
Own the data quality and reliability of the Tier-1 & Tier-2 datasets including maitaining their SLAs, TTL and consumption
Devise strategies to consolidate and compensate the data losses by correlating different sources
Solve challenging data problems with cutting edge design and algorithms
Requirements:
7+ years of extensive Data engineering experience working with large data volumes and different sources of data
Strong data modeling skills, domain knowledge and domain mapping experience
Strong experience of using SQL language and writing complex queries
Experience with using other programming languages like Java, Scala, Python
Good problem solving and analytical skills
Good communication, mentoring and collaboration skills
Nice to have:
Extensive experience in data engineering and working with Big data
Experience with ETL or Streaming data and one or more of, Kafka, HDFS, Apache Spark , Apache Flink , Hadoop
Experience backend services and familiarity with one of the cloud platform ( AWS/ Azure / Google cloud)