Business Intelligence Engineer for Retail Operations
hace 2 meses
Overview:
The Physical Stores Support Team is dedicated to implementing standard operating procedures that assist corporate divisions with product selection, onboarding, merchandising, marketing, inventory management, and pricing strategies for Amazon's physical retail locations.
Our innovative retail concepts, including Amazon Go, require a collaborative approach to enhance operational efficiency and drive business growth. Your contributions will significantly influence customer satisfaction and stakeholder confidence. Expect a dynamic environment filled with learning opportunities and skill development.
Position Summary:
We are seeking a Business Intelligence Engineer to architect and deploy scalable, automated systems for data extraction, processing, and reporting.
If you are passionate about developing data-driven solutions to address operational challenges and provide insights for business decisions, this role is tailored for you. Your expertise will help transform ideas into actionable reporting models.
Key Responsibilities:
- Possess comprehensive knowledge of available data, methods for collection, and its relevance to our operations.
- Translate fundamental business inquiries into insightful reports that address customer needs.
- Collect business requirements and clarify necessary inputs to achieve targeted outcomes.
- Collaborate closely with partner teams and business stakeholders to deliver impactful features.
- Define and manage technical roadmaps for comprehensive process automation.
- Identify and recommend enhancements for existing reporting systems.
- Create and refine query syntax for data retrieval.
- Transform data into meaningful information through descriptive analytics, aggregations, and pivoting.
- Implement and deploy data visualization tools and communication platforms (dashboards, presentations, etc.).
- Utilize data manipulation tools and validate data accuracy through testing.
- Stay updated with new technologies to foster process innovation and product transitions.
- Engage with stakeholders to comprehend business challenges and devise data-driven solutions.
- Leverage technical knowledge and product insights to guide business decisions.
- Manage expectations, estimate efforts, prioritize tasks, and communicate progress effectively.
A Day in the Life:
The Business Intelligence Engineer addresses complex challenges within the operations team, contributing to overall business success. They actively seek to understand the existing data landscape and conduct independent research. Collaboration with fellow Business Intelligence Engineers, Analysts, and Project Managers is essential.
They engage with diverse stakeholders to clarify their requirements and provide feasibility assessments. For each request, they develop a detailed implementation plan, including development milestones, time estimates, risk assessments, and user testing strategies.
They monitor progress and provide updates during meetings and through written communications. When faced with obstacles, they delve into the issues and communicate necessary actions for timely resolution.
The Business Intelligence Engineer is responsible for building reports, dashboards, queries, scripts, and macros, showcasing their technical proficiency across various domains.
Basic Qualifications:
- Experience in gathering business requirements and utilizing industry-standard business intelligence tools for data extraction, metric formulation, and report generation.
- Proficiency in a scripting language (e.g., Python, Java, or R).
- Experience in developing and maintaining fundamental data artifacts (e.g., ETL processes, data models, queries).
- Expertise in designing and implementing custom reporting systems using automation technologies.
- Familiarity with one or more analytics visualization tools (e.g., Excel, Tableau, QuickSight, MicroStrategy, PowerBI).
- Strong verbal and written communication skills, along with effective data presentation abilities.
Preferred Qualifications:
- Advanced technical degree or Bachelor's degree.
- Over 2 years of experience in data analysis and interpretation using Redshift, Oracle, NoSQL, etc.
- Knowledge of data modeling and pipeline design.
- Experience in statistical analysis and correlation analysis.
- Understanding of how to enhance code quality and optimize business intelligence processes (e.g., speed, cost, reliability).
- Able to navigate ambiguity in a fast-paced environment.
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