Business Intelligence III, Amazon

Amazon Search Relevance Customer Operations team is seeking a highly skilled and motivated Business Intelligence Engineer to join our team and take the lead to own the data foundation for the whole Search Relevance business, continuously improve the data insights quality to empower the global Search Relevance business expansion.

In this role, you will be working in one of the worlds largest and most complex data warehouse environments. You should be passionate about working with new AWS technology and complex datasets and proactively to drive the optimal data architecture with the fast changing business and technology. You will ensure we are effectively delivering high quality products that are scalable and meet business requirements.




Key job responsibilities
* Data Warehouse Design, Development, Maintenance and Optimization: Architect, build and manage secure , flexible and scalable data warehouse solutions. Ensure the iterations adapt to the ever-changing global technology and new business demand.

* Performance Optimization: Write complex and efficient SQL queries for data manipulation, transformation, and aggregation. Optimize SQL queries to improve performance and efficiency.

* ETL Process Management: Design, implement, and maintain ETL processes. Ensure accurate and efficient data integration from various sources into the data warehouse and the optimal model to fit downstream usage.

* Data Quality and Governance: Implement data quality checks and controls to ensure accuracy and integrity of data. Co-work with Risk Control Management Team to ensure the optimal data quality and compliance.

* Collaboration and Support: Work closely with Global Team to ensure the data foundation is consistent with global standards and adapted to the latest technology; Co-work with other BA, BIE, and partner to run the data ecosystem and translate data needs to robust data solutions

* Provide technical leadership and mentorship to the BI engineering team, fostering a culture of collaboration, learning, and professional development. - Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with SQL