R20211209- Data and Analytics Engineer
Milwaukee, WI 53201 US
Job Description
Data and Analytics Engineer
#R20211209
Location: Milwaukee
Duration: 6 Months+
Job Description:
- We have multiple DAE roles available on our Data team reporting to the manager to support a variety of projects across our portfolios.
- The team is currently working with the Microsoft tools (SQL Server, SSIS).
- A large focus of this role is ETL but there are also elements of data modeling and quality.
- This is a key role on our IT Data Team requiring a broad range of skills and the ability to step into different roles depending on the size and scope of the business need.
General Data Management:
- Understanding of data management concepts, data warehousing, data integration, BI, and analytics.
- Skilled in data modeling, both 3NF and dimensional, with experience in conceptual, logical, physical, and industry data modeling. Strong knowledge and experience with data architecture methodologies.
- Partner with internal business units to define information requirements and translate them into appropriate data solutions
- Performs data analysis and data profiling to gain a solid understanding of the business data
- Develop and validate source to target mappings and transformation logic
- Implement and verify end-to-end data solutions.
- Develop test plans needed to ensure a quality deliverable.
- Data blending
- Leverage existing tools to create data visualizations and mentor the business to be self- sufficient
Requirements:
- Minimum of 5 - 7 years of experience in Data Solution delivery in a complex environment working collaboratively in a team setting
- Proficient in some of the following tools: Business Intelligence tools: Alteryx, Microsoft tools (SQL Server Management Studio, SSRS, SSAS, SSIS, Power Pivot, Power Query, PowerBI)Database: SQL ServerData Query tools: SQL, T-SQLData Modeling: ER/Studio Data Architect, 3NF and dimensional modelingData Integration tools: SSIS
- Conversant in the following concepts:Data Warehousing concepts: Inmon, Kimball, Data LakeData Integration concepts and strategies: EII, ETL, EL-T, SOA, and EAIReference Data ManagementData Management and Quality: data mapping, data profiling, metadata repository, relational data modeling, master data management