Analytics Ops and Programs team in Hyderabad is looking for an innovative, hands-on and customer-obsessed Business Intelligence Engineer. 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.
Key job responsibilities
• Build scalable, efficient, and automated data processes to inform business decision making.
• Own the design, development, and maintenance of ongoing BI solutions, metrics, reports, etc. to drive key business decisions.
• Work with teams in the organization to identify opportunities and build analytical solutions that provide them with decision making capabilities and insights.
• Ensure data accuracy by validating data for new and existing tools.
• Root cause analysis and uncovering core issues using data, then assisting to create new measures for the wider Amazon team
• Manage and execute entire projects from start to finish including project management, data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.
• Collaborate with Product and Program management teams to design analytics frameworks that will support large-scale data-analysis and on-ground corrective actions.
• Collaborate with Business Analysts, Data Engineers, Software Development Engineers, and business stakeholders to understand requirements, validate data quality, and ensure deliverables align with expectations.
A day in the life
AOP (Analytics Operations and Programs) team is missioned to standardize BI and analytics capabilities, and reduce repeat analytics/reporting/BI workload for operations across IN, AU, BR, MX, SG, AE, EG, SA marketplace.
About the team
AOP is responsible to provide visibility on operations performance and implement programs to improve network efficiency and defect reduction. The team has a diverse mix of engineers, Analysts and Scientists who champion customer obsession.
BASIC QUALIFICATIONS
- Experience using Python scripting to process data for modeling
- Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field, or 2+ years of Amazon RME (BB/3P) Full Time Exempt experience
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- 2+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience
- Experience with forecasting and statistical analysis
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience with data modeling, warehousing and building ETL pipelines
- Experience using SQL (Structured Query Language) to pull data from a database or data warehouse
- 3+ years of developing automated reporting experience
PREFERRED QUALIFICATIONS
- Master's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Knowledge of Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
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