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Job Description
Job Title: Data Integration and Business Intelligence ConsultantLocation:3 days on site, Milwaukee, WIDuration: 6 months contractDescription:Responsibilities:
Owns delivery of hybrid data pipelines
Develops and maintains complex stored procedures, views, and functions
Builds and schedules SSIS packages for ETL
Integrates on-prem data sources with cloud securely and efficiently
Implements Snowflake best practices for performance, cost, and security
Leads small projects or initiatives
Provides technical guidance to junior engineers
Contributes to documentation and knowledge sharing
Monitors and optimizes pipeline performance
Builds and orchestrates batch and incremental workflows
Technical Profile:
3-5 years of experience in Data Integration / Business Intelligence in a complex environment working with SSIS
Proficient in Data Integration and Business Intelligence tools and concepts such as:
Data Integration concepts and strategies: ETL, EL-T, Data Warehousing, event-based processing
Data Integration tools: SSIS
Database: SQL Server
Data Query tools: SQL, T-SQL
Data Management and Quality: data mapping, data profiling, relational data modeling, dimensional data modeling
Building and loading relational (3NF) and dimensional data sets matching business needs
Snowflake, dbt and/or other cloud data pipeline technologies
Knowledge of Business Intelligence tools such as: Alteryx, Microsoft Power BI, SSRS, and SSAS
Working knowledge of APIs and C# coding. (would be a plus)
Qualities needed for Data role:
Good communicator who wants to work in a team environment, comfortable working collaboratively with peers
Analytical – not afraid to dive into complex code and data to troubleshoot issues
Creative problem solver who is automation focused – we're looking to not have recurring work come back to us, but to better automate or teach/train users for self service
Motivated by small quick wins and process improvement
Comfortable working in an agile environment.
Data Query tools: SQL, T-SQL
Data Management and Quality: data mapping, data profiling, relational data modeling, dimensional data modeling
Building and loading relational (3NF) and dimensional data sets matching business needs