Live opening · Posted 6 hours ago

Sr Data Analytics Engineer, Tech - Data

Uber · Hyderabad, Telangana, India
Oracle
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At a glance

The key details from the original listing.

Posted 6 hours ago
CompanyUber
LocationHyderabad, Telangana, India
SourceOracle
Listed6 hours ago

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About the role

Description supplied by the original job listing.

About the Role
We are seeking a highly skilled and experienced Sr. Data Analytics Engineer, to join our Customer Support Data (CSD) team within Uber’s Community Operations (CommOps) organization. As a key member of our team, you will be responsible for driving the design, development, and governance of data solutions to address complex business and technical challenges. Your expertise in Data engineering, data systems, and data governance will play a critical role in building scalable and efficient data platforms and tools while ensuring data integrity and compliance. This is a unique opportunity to make a significant impact on our organization, contribute to the success of our team, and champion data governance practices.
As a Senior member of the team you should be able to work through different areas of Data Engineering & Data Architecture including the following:
Data Architecture & Modeling - Understand existing sources & data models and identify the gaps and building future state architecture
Data Pipelines - Building Data Pipelines for several Data Mart/Data Warehouse and Reporting requirements
Data Governance - Build the framework for DG & Data Quality Profiling & Reporting
Data Migration - From Hive/other DBs to Cloud/other DBs and vice versa
What the candidate will do
Demonstrate strong knowledge of and ability to operationalize, leading data technologies and best practices.
Collaborate with internal business units and data teams on business requirements, data access, processing/transformation and reporting needs and leverage existing and new tools to provide solutions.
Build dimensional data models to support business requirements and reporting needs.
Design, build and automate the deployment of data pipelines and applications to support reporting and data requirements.
Research and recommend technologies and processes to support rapid scale and future state growth initiatives from the data front.
Prioritize business needs, leadership questions, and ad-hoc requests for on-time delivery.

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