Amazon Development Centre Canada ULC

Business Intelligence, Business Intel Engineer, operations

BusinessIntelligenceEngineer

CA$116–157k ~AI est. Toronto, Ontario, Canada FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“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.

Business Intelligence, Business Intel Engineer, operations
Problems you'll solve

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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