Uber Recruitment Drive; Hiring Data Engineer – Apply Now

Uber 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. Offices continue to be central to collaboration and Uber’s cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.

Name of the Organization: Uber

Requisition ID: 133792

Positions: Data Engineer - FinTech

Location: Hyderabad

Salary: As per company Norms

Educational Qualifications:

• Graduate
• Strong SQL skills
• Strong in Data Warehousing and Data Modelling concepts
• Hands on experience in Hadoop tech stack:
• HDFS, Hive, Oozie, Airflow, MapReduce, Spark.
• Programming languages - Python, Java, Scala etc.
• Experience in building ETL Data Pipelines
• Performance Troubleshooting and Tuning

Job Description:

They are seeking a strong and passionate data engineer with experience in large scale system implementation, with a focus on complex data pipelines. The candidate must be able to design and drive large projects from inception to production. The right person will work with stakeholders, analysts, scientists to gather requirements and translate them into a data engineering roadmap. Must be a great communicator, team player, and a technical 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 & orchestrate a variety of tasks such as extract, cleanse, transform, enrich & load data as per the business needs.

 

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