Enterprise Data Architect

4 weeks ago

Trenton, United States Software Technology Inc. Full time

Note: Need a local contractor who is available to come into the office for meetings. Contractor will be able to work remotely a lot of the time. This requirement will be extended 1-2 years.


Need a Sr Enterprise Data Architect focusing for building data architecture Frameworks, Standards, and Data Modeling activities defining Conceptual, Logical, Physical Analytical and Canonical models. Hands on Experience of AWS Architecture required Must have Excellent written and verbal communication skills, meticulous attention to detail, as well as the ability to understand abstract concepts. Enterprise Data Architect is responsible for designing the blueprint for NJDOL's data management framework. Collaborate with NJDOL IT management and other teams to develop a data strategy that meets departmental needs and industry requirements. Create an inventory of the data necessary to build and implement a data architecture. Envision, design data pipelines and how data will flow through the enterprise. Maintain a repository of all data architecture procedures and artifacts. Develop measures that ensure data accuracy, integrity and accessibility. Continually monitor, refine and report data management system performance. He should have strong business and communication skills as well as knowledge to act as a bridge between business operations and IT. of the big data industry. He must work with data engineers to integrate, consolidate, cleanse and structure data for use in analytics applications. The enterprise data architect must have a deep understanding of AWS services and cloud infrastructure. This skill set includes proficiency in AWS core services such as EC2, S3, VPC, and RDS, as well as an understanding of advanced services like AWS Lambda, Amazon ECS, and AWS Outposts.



Responsibilities:



  • Conduct an Assessment of the Current State of Data Systems
  • Establish the System of Record and Data Dictionary for Data Systems
  • Develop Enterprise Architecture
  • Create and construct Conceptual, Logical, and Physical Models
  • Facilitate Business Sessions to validate business taxonomy and use cases
  • Provide an initial design solution for the core data model and additional forthcoming data structures
  • Support project requirements in the modernization of Conceptual, Logical, and Physical Models
  • Define the NJDOL architecture across Conceptual, Logical, and Physical layers
  • Develop and maintain Conceptual, Logical, and Physical data models utilizing best practices and ensuring optimal query performance
  • Optimize and update Conceptual, Logical, and Physical data models to foster a new and secure data environment
  • Assist in establishing best practices for standard naming conventions
  • Coordinate activities with the EDL team, including developers and testers
  • Assist in promoting database objects from lower to higher environments
  • Lead design reviews of data models and relevant metadata to ensure consistency
  • Recommend opportunities for the reuse of data models across projects
  • Consult with Database Administrators regarding the creation of physical data schemas, referential integrity, and the fulfillment of business requirements
  • Collaborate with ETL developers, report developers, and end users on effective database utilization
  • Guide System Analysts, Engineers, Programmers, and others on project limitations, requirements, interfaces, and system integration challenges and solutions
  • Mentor DOL team members on all facets of Data Modeling


Qualifications:



  • 15+ years of experience in Business/working as a Data Architect, Data Modeler, Data Analyst
  • Understand the AWS Cloud Architecture and the basics of its infrastructure


Required Skills:



  • Data Architecture 15 Years
  • AWS Cloud Architecture 10 Years
  • AWS Glue/Athena/Storage/Lambda/Data Brew/RDS/Redshift, DMS 10 Years
  • Operational Data Modeling Skills 15 Years
  • Analytical Modeling Skills 15 Years
  • Data Governance 10 Years
  • Master Data Management 15 years
  • Metadata Management 10 Years
  • Data Cataloging 15 Years
  • Data Engineering and ETL 15 Years
  • Data Quality 15 Years
  • Excellent written and verbal communication skills 15 years
  • Strong attention to detail 15 years
  • Ability to write in explanatory and procedural styles for multiple audience 15 years
  • Skilled at prioritization and multi-tasking 5 years

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