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Business Intelligence Engineer III

Job ID: 25-09427

Pay rate range- $60/hr. - $65/hr.
Fully Onsite

Job Description:
Must Have:
SQL
Quicksight/Tableau
Correction Analysis

Business Intelligence Engineer you will be working in one of the world's largest and most complex data warehouse environments. In this role, you will primarily work on designing and building automated reporting and dashboards using complex data.

Key job responsibilities
- Develop complex queries for ad hoc requests and projects, as well as ongoing reporting.
- Design, develop and maintain scalable, automated, user-friendly systems, reports, dashboards, etc. that will support our analytical and business needs
- Design, implement, and support key datasets that provide structured and timely access to actionable business information addressing stakeholder needs.
- Interface directly with stakeholders, gathering requirements and owning automated end-to-end reporting solutions.
- Partner with analysts, data engineers, business intelligence engineers, and software development engineers across Client to produce complete data solutions.
- Simplify and automate reporting, audits, and other data-driven activities; build solutions to have maximum scale and self-service ability by stakeholders
- Proficiency with SQL queries to retrieve and analyze data. Learn and understand a broad range of Client's data resources and know how, when, and which to use.
- Estimate models, write analyses, and extract insights and provide business recommendations.

BASIC QUALIFICATIONS
- 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- 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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