Amazon Development Centre Canada ULC
Business Intelligence, Business Intel Engineer, operations
BusinessIntelligenceEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Business Intelligence Engineer at Amazon Development Centre Canada ULC. Skills: Business Intelligence, Data Engineering, Data Warehousing, Data Visualization. Apply mining, quantitative analysis, and statistical models. Understand customer interactions”
What You'll Achieve.
Provide insights to inform business decision making; Increase efficiency
Industry & Context.
Quantitative analysis; Statistical models; Performance optimization; Troubleshooting ETL issues
What They're Looking For.
Must Have
3+ years analyzing data with Redshift, Oracle, NoSQL, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with data visualization using Tableau, Quicksight, Experience writing complex SQL queries, Experience in Statistical Analysis packages such as R, SAS, Matlab, Experience using SQL to pull data, Scripting experience (Python) to process data
Nice to Have
Experience with AWS solutions, Experience in data mining, Experience in ETL, Experience using databases in a business environment with large-scale, complex datasets
What You'll Do.
quantitative analysis
and statistical models
Understand customer interactions
Identify ways to improve customer experience
Build scalable solutions
Build self-serve platforms
Provide insights to inform business decision making
Optimize performance of business-critical queries
Deal with ETL job-related issues
Gather data requirements
Understand data requirements
Achieve high quality data ingestion
Build systems that process data
Build systems that transform data
Build systems that store data
Dive deeply into technical details
Drive constructive technical discussions
Extract data from various heterogeneous data sources
Combine data from various heterogeneous data sources
Build end-to-end designs
Evaluate end-to-end designs
Create interactive visual dashboards
Write clear documentation
Write architecture documents
Create an engineering roadmap
Explore AWS technologies
Learn AWS technologies
Provide new capabilities
Innovate using big data techniques
How You'll Work.
Team & Collaboration
Work with business analysts; Work with data engineers; Work with engineering teams
Communication Scope
Business communication; Technical discussions; Documentation; Architecture documents
Process & Methodology
Roadmap planning
Full Job Description
The Supply Chain Optimization Technologies (SCOT) organization, has an immediate need for a creative business intelligence engineer (BIE) with a passion for building systems that have a measurable impact. The right candidate will be innovative and technically versatile. You will have the opportunity to work with one of the largest and most complex warehouses in the world to gather insights using from across Amazon. As a BIE, you should be an expert in the architecture of data warehouse solutions for the enterprise using multiple platforms. You should excel in the design, creation, management, and business use of extremely large datasets. Excellent business and communication skills are required to work with business analysts and data engineers to understand how best to design reporting and analytics data systems. Key job responsibilities Apply mining, quantitative analysis, and statistical models to understand how our customers interact with us and identify ways to improve the customer experience and meet our goals • Build scalable solutions and self-serve platforms that will provide insights to inform business decision making • Optimizing the performance of business-critical queries and dealing with ETL job-related issues • Gathering and understanding data requirements, working with the team to achieve high quality data ingestion and building systems that can process, transform, and store the data in various relational and non-relational stores • Dive deeply into technical details (e.g., key dependencies, design choices, operability, etc.) with engineering teams and drive constructive technical discussions. Extracting and combining data from various heterogeneous data sources • Build and evaluate end-to-end designs for strengths and weaknesses (quality, scalability, latency, security, performance, data integrity, etc.) • Create interactive visual dashboards with Tableau and QuickSight • Write clear documentation, architecture documents and create an engineering road
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