Demo

Data Architect with AFS Loan systems

Bean Infosystems LLC
Cincinnati, OH Contractor
POSTED ON 4/15/2025 CLOSED ON 4/17/2025

What are the responsibilities and job description for the Data Architect with AFS Loan systems position at Bean Infosystems LLC?

Job Type: W2 Contract


Job Title: Data Architect / Principal Data Engineer IV

Location: Cincinnati, OH

Duration: 12 months with possible extensions


 

 TECHNICAL SKILLS Must Have:

  • AFS OR LOAN BACKGROUND REQUIRED
  • Business Intelligence - Data Engineering
  • - Conceptual understanding of one or more of the following disciplines preferred big data technologies and distributions, metadata management products, commercial ETL tools, BI and reporting tools (visualization), messaging systems, data warehousing, SQL, Java (language and run time environment), major version control systems, continuous integration/delivery tools, infrastructure automation and virtualization tools, data testing, major cloud, or rest API design and development.
  • • DBT/Snowflake 4-5 years • Strong Communications Skills • Able to run meetings • Problem Solving and Critical Thinking

Nice To Have

  • • Analytical • DataStage • Dataiku • AFS system application (AFS Level III or Vision)

 


Qualifications:

·         Technical Degree or related work experience

·         Experience gathering and analyzing system requirements

·         Knowledge of data mining and segmentation techniques

·         Knowledge of programming languages (C, PHP, ect)

·         Expertise database technologies (SQL, Oracle, ect)

MINIMUM KNOWLEDGE, SKILLS, AND ABILITIES REQUIRED:

·         Bachelor's degree in Computer Science/Information Systems or equivalent combination of education and experience.

·         Must be able to communicate ideas both verbally and in writing to management, business and IT sponsors, and technical resources in language that is appropriate for each group.

·         Fundamental understanding of distributed computing principles

·         Knowledge of application and data security concepts, best practices, and common vulnerabilities.

·         Conceptual understanding of one or more of the following disciplines preferred big data technologies and distributions, metadata management products, commercial ETL tools, BI and reporting tools (visualization), messaging systems, data warehousing, SQL, Java (language and run time environment), major version control systems, continuous integration/delivery tools, infrastructure automation and virtualization tools, data testing, major cloud, or rest API design and development.

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