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22

April

Business Intelligence Engineer

Amazon Corporate Services Pty - Sydney, NSW

IT
Source: uWorkin

JOB DESCRIPTION

DESCRIPTION

Amazon is looking for a highly analytical Business Intelligence Engineer to join the World Wide Benchmarking Team. Our mission is to develop, deploy, and sustain scalable mechanisms to drive WW Operations to achieve best at Amazon performance. You will deliver results based on analyzing, evaluating and surfacing opportunities with your cross-disciplined team to senior leadership globally.
As a Business Intelligence Engineer, you will generate insights that will guide operational excellence and business strategy for our customers. Data analysis is at the core Amazon’s culture, and your work will have a direct impact on decision-making and strategy for our organization. You will be gathering operational insights, run statistical analysis, mining data, making recommendations, and helping senior leaders make key business decisions. You will have the opportunity to work with large and diverse data sets to gather insights using data from across AWS Infrastructure.
The ideal candidates will have excellent analytical and statistical abilities, outstanding business acumen and judgment, intense curiosity, strong technical skills, and superior written and verbal communication skills. They will have a strong bias toward data driven decision-making. They will be a self-starter, comfortable with ambiguity, able to think big and be creative (while paying careful attention to detail). Enjoys working in a fast-paced dynamic environment. If you are excited about data, are results oriented, and want to join a growing analytics team within Amazon, this role is for you.

Are you up for the challenge? #Letsdothis

Responsibilities:
Design, develop and maintain scaled, automated, user-friendly systems, statistical analysis and prediction, reports, dashboards, etc. that will support the needs of the business.
Apply deep analytic and business intelligence skills to extract meaningful insights and learning from large and complicated data sets using the appropriate statistical forecasting model and Machine Learning models.
Be hands-on with ETL to build data pipeline to support automated reporting.
Serve as liaison between the business and technical teams to achieve the goal of providing actionable insights into current business performance, and ad hoc investigations to support future improvements or innovations. This will require data gathering and manipulation, problem solving, and communication of insights and recommendations.
Build various data visualizations to tell the story of business trends, patterns, and outliers through rich visualizations.
Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.

BASIC QUALIFICATIONS

· BA/BS in Computer Science, Engineering, Mathematics or related experience.
· 3+ years of relevant work experience in data science, business analytics, business intelligence (BI), or comparable experience in big data environments.
· 3+ years of experience in data mining and data-set preparation using SQL.
· 3+ years of experience with Power Bi, Quicksight, or other relevant data visualization software.
· Knowledge of data warehouse technical architecture, infrastructure components, ETL and reporting/analytic tools and environment.
· Be self-driven, details-oriented, and show ability to deliver on ambiguous projects with incomplete or dirty data.
· Proficient understanding of data warehousing, data modelling methods.
· Fluency with statistical analytics and programming languages such as R, Python, Ruby, etc.

PREFERRED QUALIFICATIONS

· 5+ years of experience in a data engineer or BIE role with a technology company.
· Graduate degree in Computer Science, Engineering, Mathematics, related technical field
· Strong verbal/written communication and data presentation skills, including an ability to effectively communicate with both business and technical team, and senior management as required.
· Experience using Cloud Storage and Computing technologies such as AWS Redshift, S3, Hadoop, etc.
· Experience working in large data warehouse environments.
· Experience conducting large scale and complex data analysis to support business decision making.
· Experience with Machine Learning models.