Amazon Hiring Drive 2024: Amazon Hiring Drive 2024 for its Business Intel Engineer I, AOP. Amazon Drive organizes off-campus drives for candidates in any batch. To apply, candidates should have a Master’s degree or Advanced technical degree. if you are interested, please apply as soon as possible.
Company Name: Amazon
Role: Business Intel Engineer I, AOP
Location: Hyderabad
Experience: 2+ years
Qualification: Master’s degree, or Advanced technical degree
Batch: Any
Job Type: Full Time
Salary: 14.0 to 26.0 LPA (Expected)
Amazon Hiring Drive 2024
Job Description:
- Amazon Transportation team is looking for an innovative, hands-on and customer-obsessed Business Analyst for Analytics team. Candidate must be detail oriented, have superior verbal and written communication skills, strong organizational skills, excellent technical skills and should be able to juggle multiple tasks at once.
- Ideal candidate must be able to identify problems before they happen and implement solutions that detect and prevent outages. The candidate must be able to accurately prioritize projects, make sound judgments, work to improve the customer experience and get the right things done.
- This job requires you to constantly hit the ground running and have the ability to learn quickly. Primary responsibilities include defining the problem and building analytical frameworks to help the operations to streamline the process, identifying gaps in the existing process by analyzing data and liaising with relevant team(s) to plug it and analyzing data and metrics and sharing update with the internal teams.
Requirements:
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with building and maintain basic data artifacts (e.g. ETL, data models, queries)
- Experience with scripting language (e.g., Python, Java, or R)
- 2+ years of ecommerce, transportation, finance or related analytical field experience
- Master’s degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
Responsibility:
- Apply multi-domain/process expertise in day to day activities and own end to end roadmap.
- Translate complex or ambiguous business problem statements into analysis requirements and maintain high bar throughout the execution.
- Define analytical approach; review and vet analytical approach with stakeholders.
- Proactively and independently work with stakeholders to construct use cases and associated standardized outputs
- Scale data processes and reports; write queries that clients can update themselves; lead work with data engineering for full-scale automation
- Have a working knowledge of the data available or needed by the wider business for more complex or comparative analysis
- Work with a variety of data sources and Pull data using efficient query development that
- requires less post processing (e.g., Window functions, virt usage)
- When needed, pull data from multiple similar sources to triangulate on data fidelity
- Actively manage the timeline and deliverables of projects, focusing on interactions in the team
- Provide program communications to stakeholders
- Communicate roadblocks to stakeholders and propose solutions
- Represent team on medium-size analytical projects in own organization and effectively communicate across teams
- Solve ambiguous analyses with less well-defined inputs and outputs; drive to the heart of the problem and identify root causes
- Have the capability to handle large data sets in analysis through the use of additional tools
- Derive recommendations from analysis that significantly impact a department, create new processes, or change existing processes
- Understand the basics of test and control comparison; may provide insights through basic statistical measures such as hypothesis testing
- Identify and implement optimal communication mechanisms based on the data set and the stakeholders involved
- Communicate complex analytical insights and business implications effectively
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