Data and Analytics Engineer

1 week ago

Milwaukee, United States Element6Talent Full time

Element6's client is looking for a Data and Analytics Engineer to join their team in Milwaukee, WI. This is a key role on their 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. The self-motivated candidate will have proven experience architecting successful data solutions on key projects in a collaborative environment. Success will come from being able to prioritize, deliver value incrementally, problem solve, and manage changing priorities. You will work closely with the Company's business partners and interface with both technical and non-technical colleagues.


Responsibilities:

Data Architecture

  • Specialize 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.
  • Apply the appropriate level of modeling theory, pattern recognition, and abstractions to architect and design a pragmatic solution that functionally meets the business and technical requirements.
  • Partner with internal business units to define information requirements and translate them into appropriate data solutions.
  • Collaborate with IT and business partners to lead data discovery, profiling, analysis, and quality assessments in order to obtain clear information requirements.
  • Develop and validate source to target mappings and transformation logic required to support business needs. Understand the importance of capturing data lineage.
  • Architect, implement and verify end-to-end data solutions.
  • Develop test plans needed to ensure a quality deliverable. Participate in validation testing, coordinate user acceptance testing and training to ensure the final implementation enables the user to solve their business problem.

General Data Management

  • Play a critical role in architecting our data and analytics solution landscape
  • Demonstrate competence, experience, knowledge, understanding, and advocacy of data management concepts, data warehousing, BI, and analytics.
  • Demonstrate ability to perform appropriate level of strategic thinking by viewing initiatives both within the immediate project context as well as the overall architectural vision.
  • Participate and/or Lead in data architectural design and strategy discussions.

Data Delivery

  • Work with the business users to conduct data discovery engagements and can quickly identify, and prototype, a solution that brings together multiple data sources into one coherent concept and understanding. (data blending)
  • Leverage existing tools to create data visualizations and mentors the business to be self-sufficient.

Collaborate

  • Identify and communicate project risks and impediments and proactively work with other members of the Analytics team to complete high-value deliverables as identified by business partners and team leadership.
  • Partner with Analytics team members to translate business and functional requirements into technical designs
  • Strive to understand the data consumption needs of the business community, as well as the problems faced by business users involving the access and use of data
  • Help Analytics teams develop solutions that enable businesses to capitalize on business insights and drive toward gaining a competitive advantage


Requirements:

  • Minimum of 3-5 years of experience in Data Solution delivery in a complex environment working collaboratively in a team setting
  • Proficient in Data Solution tools and concepts such as:
  • Business Intelligence tools: Microsoft tools (SQL Server Management Studio, SSRS, SSAS, Power Pivot, Power Query, PowerBI), Alteryx
  • Database: SQL Server
  • Data Query tools: SQL, T-SQL
  • Data Management and Quality: data mapping, data profiling, metadata repository, relational data modeling, master data management
  • Data Modeling: ER/Studio Data Architect, 3NF and dimensional modeling
  • Data Warehousing concepts: Inmon, Kimball, Data Lake
  • Data Integration concepts and strategies: EII, ETL, EL-T and EAI

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