Data Engineer II

Uber · Hyderabad

  • Experience5–9 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelsenior
  • Posted2 Sept 2026
Apply for this job

About Uber

Uber is hiring in Hyderabad in automotive mobility. This role looks for around 5+ years of experience.

Skills

  • Python
  • SQL
  • Java
  • Scala
  • Spark
  • Flink
  • MapReduce
  • Presto
  • data modelling
  • ETL
  • data warehousing
  • Hadoop
  • HDFS
  • Hive
  • Oozie
  • Airflow
  • performance tuning

The role

A data engineer at a large-scale mobility marketplace designs complex data pipelines and builds data warehousing solutions using Python, SQL, and Spark for production analytics systems. Data modelling and ETL pipelines support cross-functional product and technology initiatives.

Full job description

We are seeking a strong and passionate data engineer with experience in large-scale system implementation, with a focus on complex data pipelines. The candidate should be able to design and drive large projects from inception to production. The right person will work with cross-functional businesses and technology partners to gather requirements and translate them into a data engineering roadmap. Must be a great communicator, a standout teammate, and a technology powerhouse.

Responsibilities:

Collaborate with engineering/product/analyst teams across tech sites to collectively accomplish OKRs to take Uber forward.

Enrich data layers to effectively deal with the next generation of products, which are a result of Uber's big, bold bets.

Design and build data pipelines to schedule and orchestrate a variety of tasks such as extracting, cleansing, transforming, enriching, and loading data as per the business needs.

Requirements:

5+ years total technical software engineering experience in one or more of the following areas:

Programming and scripting languages (e. g., Python, SQL, Java/Scala).

Big data frameworks (e. g., Spark, Flink, MR, and Presto), data modelling, and writing ETLs.

Designing end-to-end data solutions and architecture.

Strong SQL skills.

Strong in data warehousing and data modelling concepts.

Hands-on experience in the Hadoop tech stack: HDFS, Hive, Oozie, Airflow, MapReduce, and Spark.

Programming languages - Python, Java, Scala, etc.

Experience in building ETL data pipelines.

Performance Troubleshooting and Tuning.