Job Description

About the Role

We are looking for talented Data Engineers who are passionate about data engineering and have strong experience in building scalable data pipelines. As a Data Engineer at Uber you will play a leading role in designing and building datasets that power analytics for teams across Uber. You will also be working closely with Data Analysts, Data Scientists and stakeholders to gather requirements and translate them into a data engineering roadmap for the team.




Minimum Qualifications




4+ years of relevant industry experience.


4+ years of SQL experience.


4+ years of python/java/scala experience.


2+ years of data modeling experience.


Experience designing and deploying high performance systems with reliable monitoring and logging practices.


Excellent communication skills, both written and verbal.





Preferred Qualifications




Experience with designing and implementing real-time pipelines.


Experience with SQL performance tuning and E2E process optimization.


Experience with workflow management engine e.g Airflow.


Experience with a cloud platform GCP preferred.


Experience querying massive datasets using Spark, Presto, Hive, Impala, etc.


Experience with data quality and validation.


Experience with more than one coding language.


Responsibilities




Develop and automate large scale, high-performance data processing systems.


Lead data engineering projects to ensure pipelines are reliable, efficient & maintainable


Design data models for optimal storage and retrieval and to meet business requirements.


Own and Drive complex architectural changes


Should be self-motivated and passionate about bringing efficiency into the system through optimizations.


Should be able to raise the technical bar for other engineers by proposing and driving innovative ideas.


About the team




You will be joining the IT Eng - data team which is responsible for building and maintaining datasets for people analytics. We extract data from 10+ data sources and build a consolidated data view for data analytics and reporting to our leadership. We have also been growing our data engineering practices to enable leadership to make right decisions by building solid people data foundations.