Experience gathering business requirements, using industry standard business intelligence tool(s) to extract data, formulate metrics and build reports
- Experience with scripting language (e.g., Python, Java, or R)
- Experience building and maintaining basic data artifacts (e.g., ETL, data models, queries)
- Experience in designing and implementing custom reporting systems using automation tools
- Experience with one or more analytics visualization tools (e.g., Excel, Tableau, QuickSight, MicroStrategy, PowerBI)
- Excellent verbal/written communication skills and data presentation skills
The Physical Stores Support Team executes SOPs to aid Corporate teams with product selection & onboarding, merchandising, marketing, inventory and pricing functions for Amazon branded brick and mortar stores.
Our stores have innovative concepts (including Amazon Go!). You'll be part of a team working to operate, scale, and invent to support business success and growth. Your work will have a direct impact on the customer experience and stakeholder trust. Expect fun, a learning curve, and opportunities to sharpen your skills and grow.
Our team is hiring a Business Intelligence Engineer to design and implement scalable, automated infrastructure for data extraction, processing and delivery. If you are interested in creating data solutions to visualize/solve Operations team challenges and answer business questions, we have the career for you! We need you to help us go from idea to functional model for our reports.
Key job responsibilities
- Have in-depth knowledge of the data available, how to collect it, and understand how it applies to our business.
- Translate basic business problem statements into reports that answer customer questions.
- Gather business requirements and inform of inputs needed to achieve the desired results.
- Work closely with partner teams and business stakeholders to deliver features.
- Define and management of technical roadmaps for end to end process automation.
- Periodically identify opportunities for optimization in existing reporting.
- Create and modify query syntax.
- Convert data to information through basic descriptions, aggregations, and pivots.
- Implement/deploy data visualization or communication tools (dashboards, decks, etc.).
- Utilize basic data-manipulation tools and test data to determine accuracy.
- Learn new technology to support process innovation and product migrations.
- Communicate with stakeholders to understand business problems and define logic that can be solved with data, statistics, and scripting.
- Uses technical expertise and product knowledge to consult on business decisions.
- Manage expectations, estimate effort, prioritize workload and communicate on status.
A day in the life
Our Business Intelligence Engineer tackles complex challenges on a Operations team and contributes to the success of the business. They proactively seek to understand the existing data infrastructure and research independently. They collaborate with other Business Intelligence Engineers, Analysts and Project Managers.
They meet with diverse stakeholders to understand their problem statements, requirements and advise on feasibility. For each request they create an implementation plan and timeline; including development milestones, time estimations, risk and mitigation plans, and user testing. They track progress and share status updates in meetings and in written communications.
They dive deep on roadblocks and inform of actions needed to resolve on a timely manner.
The Business Intelligence Engineer builds reports, dashboards, queries, scripts, macros, etc., demonstrating their technical skills in a number of areas.
Heredia, H, CRI
- Advanced technical degree, or Bachelor's degree
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
- Knowledge of how to improve code quality and optimizes BI processes (e.g. speed, cost, reliability)
- Ability to deal with ambiguity in a fast-paced environment