Business Intelligence Analyst
3 weeks ago
The Business Intelligence Engineer will be responsible for developing models and tools, conducting statistical analyses, and creating tailored models and dashboards. This role will be instrumental in creating a reliable and scalable infrastructure for ongoing reporting and analytics.
Key Responsibilities
- Enable decision-making by retrieving and aggregating data from multiple sources to present it in a digestible and actionable format
- Work with cross-functional teams to identify gaps and trends
- Analyze large data sets using a variety of database query and visualization tools
- Provide technical expertise in extracting, integrating, and analyzing critical data
- Anticipate, identify, structure, and solve critical problems
- Design and develop key performance metrics and indicators using standardized and custom reports
- Perform ad hoc analysis to quickly solve time-sensitive operational issues and business cases
- Clearly communicate any potential data discrepancies and/or reporting downtime, including specific root cause, steps to resolution, and resolution date to a large end-user base
- Partner with subject matter experts to document and translate business requirements into technical requirements
- Manage multiple projects and proactively communicate issues, priorities, and objectives
About the Team
The Ring Data Science and Engineering (RDSE) Org is responsible for the data strategy, architecture, governance, science, and software services Ring teams use to inform business strategy or power experiences with data. The central Data Science and Analytics team (within RDSE and the team where this role is based) is responsible for core business metrics, shared data models, AI/ML models, business intelligence dashboards, and business analysis/science support.
Requirements
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing, and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS, and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
Preferred Qualifications
- 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
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