Data Engineer II
Description For Data Engineer II
Uber is seeking a passionate Data Engineer II to join their team in Hyderabad, India. This role focuses on implementing large-scale data systems and complex data pipelines. The ideal candidate will collaborate with stakeholders, analysts, and scientists to gather requirements and translate them into actionable data engineering roadmaps.
The position requires expertise in data warehousing, SQL, and the Hadoop technology stack, including HDFS, Hive, Oozie, Airflow, MapReduce, and Spark. You'll work with various programming languages such as Python, Java, and Scala to build robust ETL pipelines and data solutions.
As a Data Engineer II, you'll be responsible for enriching data layers, designing pipelines, and collaborating across teams to achieve organizational OKRs. The role offers opportunities to mentor junior team members and drive innovative solutions in an agile environment.
Uber maintains a hybrid work model, expecting employees to spend at least half of their work time in the office, emphasizing the importance of in-person collaboration and cultural identity. The company welcomes diverse backgrounds and individuals passionate about building the future of independent movement.
This position is perfect for someone who combines technical expertise with strong communication skills, enjoys collaborative work, and has a drive for optimization and innovation in data engineering solutions.
Responsibilities For Data Engineer II
- Collaborate with engineering/product/analyst teams across tech sites to collectively accomplish OKRs
- Enrich data layers to effectively deal with the next generation of products
- Design and build data pipelines to schedule & orchestrate tasks such as extract, cleanse, transform, enrich & load data
- Mentor junior team members technically
- Drive big efforts in collaboration with other engineers or team members
Requirements For Data Engineer II
- 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
- Experience in building ETL Data Pipelines
- Performance Troubleshooting and Tuning
- Experience with DW or BI or OLAP tools like Anaplan, TM1, Hyperion
- Experience building high-quality end-to-end data solutions in an agile environment
- Should be self-motivated and passionate about bringing efficiency through optimizations
- Should be able to raise the bar for other engineers by proposing and driving innovative ideas
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