Business Intelligence Engineer for Retail Operations
hace 2 meses
About the Role
The Physical Stores Support Team is dedicated to executing standard operating procedures that assist corporate teams with various functions, including product selection, onboarding, merchandising, marketing, inventory management, and pricing strategies for Amazon's physical retail locations.
As part of a team that supports innovative retail concepts, such as Amazon Go, you will play a crucial role in driving operational success and growth. Your contributions will directly influence customer experiences and build stakeholder trust. Expect a dynamic work environment filled with learning opportunities to enhance your skills.
Position Overview
We are seeking a Business Intelligence Engineer to develop and implement scalable, automated systems for data extraction, processing, and delivery. If you are passionate about creating data-driven solutions to address operational challenges and provide insights for business inquiries, this role is tailored for you.
Key Responsibilities
- Possess comprehensive knowledge of available data, methods for collection, and its relevance to our business.
- Transform basic business inquiries into insightful reports that address customer needs.
- Collect business requirements and clarify necessary inputs to achieve desired outcomes.
- Collaborate closely with partner teams and business stakeholders to deliver impactful features.
- Define and manage technical roadmaps for end-to-end process automation.
- Identify optimization opportunities within existing reporting frameworks.
- Create and adjust query syntax as needed.
- Convert raw data into meaningful information through descriptive analytics, aggregations, and pivoting.
- Implement and deploy data visualization tools and communication resources (dashboards, presentations, etc.).
- Utilize basic data manipulation tools and validate data accuracy through testing.
- Stay abreast of new technologies to foster process innovation and support product transitions.
- Engage with stakeholders to comprehend business challenges and devise data-driven solutions using statistics and scripting.
- Leverage technical expertise and product knowledge to inform business decisions.
- Manage expectations, estimate efforts, prioritize tasks, and communicate progress effectively.
A Day in the Life
As a Business Intelligence Engineer, you will tackle complex challenges within the operations team, contributing significantly to the overall success of the business. You will proactively explore the existing data infrastructure and conduct independent research. Collaboration with fellow Business Intelligence Engineers, Analysts, and Project Managers will be essential.
You will engage with diverse stakeholders to understand their requirements and provide guidance on feasibility. For each request, you will develop an implementation plan that includes timelines, development milestones, risk assessments, and user testing strategies. Regular progress tracking and status updates will be part of your routine.
In this role, you will build reports, dashboards, queries, scripts, and macros, showcasing your technical skills 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 building and maintaining fundamental data artifacts (e.g., ETL processes, data models, queries).
- Experience in designing and implementing custom reporting systems with automation tools.
- 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 platforms like Redshift, Oracle, or NoSQL.
- Knowledge of data modeling and pipeline design.
- Experience with statistical and correlation analysis.
- Understanding of code quality improvement and optimization of BI processes (e.g., speed, cost, reliability).
- Able to navigate ambiguity in a fast-paced environment.
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