Data Architect with Erwin Data Modelling & Snowflake Exp. Position in Chicago, IL (Onsite)

Job Title : Data Architect with Erwin Data Modelling & Snowflake Exp. Location : Chicago, IL (Onsite) Duration : Long Term Contract Job Description: Mandatory Skills: Data Modelling using Erwin data modelling tool, SQL/T-SQL, Cloud Data Platform (Snowflake), Data Warehousing Concepts, Data Architecture definition NEED 15+YRS EXPEREINCE ENTERPRISE ARCHITECT LEVEL RESOURCE. looking for local resource based in Chicago or near by suburbs who can commute onsite location Able to work and provide guidance to the customer regarding the technical selection and design of the enterprise architecture Be able to work and provide recommendations at CXO level and have ability to work across multiple projects help customer prioritize projects and achieve data quality and efficiency in data ingestion Data Architect: Sr. Data Architect should have working understanding and application of dimensional and relational modeling techniques and methodologies and will need to support data initiatives and ensure optimal data delivery is consistent throughout ongoing projects. You will engage in supporting the data needs of multiple teams, systems and products for on-prem and cloud implementations. Essential responsibilities include participating in analysis sessions with the user community to capture data requirements clearly, completely and correctly, include identifying, analyzing and translating business requirements into logical and physical database design and final data product. Successful candidate delivers data architecture, modeling, specifications and data profiling services to the BI / DW / Data Engineering projects from the requirements through design, development, test and implementation. Responsibilities · Work with partners including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data acquisition needs · Orchestrate large, complex data sets that meet functional/non-functional business requirements for on-prem and Azure projects · Participating in analysis sessions with the user community to capture data requirements clearly, completely and correctly and translate requirements into a viable data models in complex, multi-application environments · Collaborate with data engineering, and analytics talent to strive for greater functionality in our data systems. · Implement operational and dimensional logical and physical design using modeling tools for Data Marts, Data Warehouse and Azure cloud data solutions · Define and implement best practices in the areas of data architecture, data warehousing, ETL/data integration, data engineering and advanced analytics · Create, review and communicate the Source Systems Analysis and Source-to-Target mapping across Staging, integration and presentation layers, conduct Data analysis/profiling using SQL and / or T-SQL and reverse engineering of data and data cataloging within on-prem and Azure Synapse environments · Identify and document data integration issues, challenges such as duplicate data, non-conformed data, and unclean data · Demonstrate deep familiarity with MS SQL Server database technologies (MS SQL 2016 and above) and proficiency in SQL/T-SQL in both on-prem and Azure cloud · Understand Business Intelligence solutions, present strong knowledge of relational and multi-dimensional database architectures, database lifecycle design and application development · Work with team members to design and maintain a corporate data architecture that allows the data warehouse to evolve with the business · Deliver quality work on time with multiple, competing priorities · Effective communication skills · Ability to work independently and as part of a team · Ability to execute effectively on the agreed upon decisions · Ability to read/interpret documents including process, procedure, and technical manuals. · Excellent organizational skills with the ability to work effectively on multiple priorities with firm deliverable dates. · Bachelor’s Degree in Information Systems or related discipline preferred