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Senior Software Engineer I - Data Engineering

Data, Engineering en Bangalore, India

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 600 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.

About the Role


As a Senior Software Engineer - Data, at Uber you will play a leading role in scaling the global data warehouse to power analytics for teams across Uber. You are a self-starter with extensive industrial experience in SQL, Data Modeling, and ETL pipeline design.

You have deep experience implementing ETL pipelines in Hive or another MPP database architecture. You are comfortable with Spark and Presto having used one or both frequently to process very large volumes of data. You possess at least a working knowledge on a platform for streaming analytics. You are comfortable coding in Python, Java, or Scala.

You have demonstrated strong competency in reliably operating 100s of ETL pipelines with adherence to strict SLAs and quickly root-causing and correcting complex data problems. Peers describe you as the go-to person for the most challenging data ingestion and modeling problems. You actively mentor junior team members and attract others inside and outside your company to join your team. Detail-orientation, thoroughly tested code, 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.

Required skills:

  • 8+ years expertise creating and evolving dimensional data models & schema designs to structure data for business-relevant analytics.
  • 8+ years hands-on experience using SQL to build and deploy production-quality ETL pipelines.
  • 3+ years experience ingesting and transforming structured and unstructured data from internal and third party sources into dimensional models.
  • 3+ years experience writing and deploying Python, Scala, or Java code.
  • 3+ years hands-on experience using Hadoop, Hive, Vertica or another MPP database system like AWS Redshift or Teradata.
  • 2+ years experience building and operating realtime streaming data pipelines using Spark Streaming, or Flink
  • Track record of successful partnerships with product and engineering teams resulting in on-time delivery of impactful data products.
  • Demonstrated ability to think strategically about business, product, and technical challenges and implement data solutions which scale to meet future needs.
  • Experience developing scripts and tools to enable faster data consumption.

Preferred skills:

  • In-depth understanding of with Kimball’s data warehouse lifecycle.
  • Extensive experience with real-time data ingestion and stream processing.
  • Demonstrated familiarity with industry-leading Big Data ETL practices.

The Customer Obsession team aims to provide a great experience to all of Uber's customers. Whether you are a rider or an eater, or a driver-partner, we want to ensure that all your experience is flawless. We build the entire customer support infrastructure for the fastest growing startup in the world ensuring ensuring a smooth ride for our all of our customers, and efficient growth for Uber. Our mission is to capture the hearts of riders, eaters and drivers, and we set out to do that every single day.

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En Uber no solo aceptamos la diferencia; la celebramos, la apoyamos y la valoramos para beneficio de nuestros empleados, de nuestros productos y de nuestra comunidad. Uber se enorgullece de ser un lugar de trabajo con igualdad de oportunidades y es un empleador de acción afirmativa. También estamos comprometidos con el empleo en igualdad de oportunidades sin considerar raza, color, origen familiar, religión, sexo, origen nacional, orientación sexual, edad, ciudadanía, estado civil, condición de discapacidad, identidad de género o estado de Veterano.