AMAZON Hiring Business Intelligence Engineer Jobs In Singapore Salary Upto 80000$/Year Apply Now

Company:	AMAZON
Job Role:	Business Intelligence Engineer
Experience:	(0to3years):
Vacancy:	8+
Qualification:	Degree in Computer Science
Salary:	80000$/Year
Location:	Singapore
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Apply Mode:	(Online)
Deadline:	Not Mentioned

About the Company:

                                      

Amazon is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. Amazon strives to be Earth’s most customer-centric company, Earth’s best employer, and Earth’s safest place to work. Customer reviews, 1-Click shopping, personalized recommendations, Prime, Fulfillment by Amazon, AWS, Kindle Direct Publishing, Kindle, Career Choice, Fire tablets, Fire TV, Amazon Echo, Alexa, Just Walk Out technology, Amazon Studios, and The Climate Pledge are some of the things pioneered by Amazon.

Job Description:

Job summary

Global Transportation Services (GTS) sits at the center of Amazon's massive Outbound Transportation Supply Chain and the GTS Finance Technology team drives the data engineering and analytics solutions to supporting the financial analytics use cases for GTS. Our team is seeking an experienced Business Intelligence Engineer with excellent statistical and analytical abilities along with data engineering skills. Within this role you will have unique opportunities to work alongside engineers, product managers, data scientists, program managers and finance leaders to help build next gen analytics and data driven reporting supported via one of the largest finance data warehouses.

In this role, you will be helping scale the outbound supply chain cost allocation/analytics which spans across EU. You will work closely with product managers to design and implement new cost allocation strategies, work with engineers across the network to assess impact of new program rollouts & help build operational and anomaly detection reporting solutions. Amazon has a culture of being builders and you will get to use the latest technology stack offered via AWS and internal amazon tools to help scale big and fast.

The ideal candidate is a motivated self-starter that can work independently in a fast paced, ambiguous environment with limited supervision. You must be a fast learner who can quickly absorb the nuances of Amazon's transportation services. You need to be analytical in your decision making, with a demonstrated ability to drive issues to completion.

Key job responsibilities

· Engage with Business customers to gather requirements and deliver scalable BI solutions that provide accurate results and support business decision making.

· Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.

· Build ETL, data pipeline jobs, appropriate aggregations, and automated delivery.

· Apply your deep analytic and business intelligence skill to extract meaningful insight and learning from large and complicated data set

· Design data models on varied database platforms like Redshift, MySQL or object based data stores.

BASIC QUALIFICATIONS

• Degree in Computer Science, Engineering, Math, Statistics or related discipline
• 3+ years of relevant experience in business intelligence role
• Experience with Data warehousing and BI tools/technology
• Solid business acumen, ability to bridge business and tech sides
• Experience with SQL, Relational databases, and/or Big Data
• Experience with data warehousing concepts and coding in at least one analytical programming language (R, Python)
• Experience using data visualization tools such as QuickSight, Tableau and Excel

PREFERRED QUALIFICATIONS

• Experience managing Quicksight / Tableau server implementation along with associated knowledge of permissions/ security management.
• Experience in building cloud native solutions
• Shell scripting experience is a plus
• Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operation

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