Enterprise Data Architect
Enterprise Data Architect
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Salary Not Disclosed
1 Vacancy
Job Description
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.
KNOWLEDGE AND EXPERIENCE
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
Hands on Experience and Expertise in using AWS tools: AWS glue data brew AWS LambdaAWS S3 AWS Dynamo DB AWS RDS Athena Redshift DMS
Hands on Experience andExpertise in creating and automating Data pipelines using AWS services.
Expertise in Data Management Principles
Expertise in Master Data Management Principles
Expertise in Data Governance Concepts
Expertise in Data Engineering Methodologies
Expertise in Data Modeling Solution Architecture Master DataManagement (MDM) Gathering and Systems Analysis in State
Proficient in NoSQL Relational MDM Data Modeling.
Experience in Data Governance with Collibra
Experienced in working with different SoftwareDevelopment Methodologies.
DUTIES and 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 usecases
Provide an initial design solution for the core data model andadditional forthcoming data structures
Support project requirements in the modernization of ConceptualLogical and Physical Models
Define the NJDOL architecture across Conceptual Logical and Physicallayers
Develop and maintain Conceptual Logical and Physical data modelsutilizing best practices and ensuring optimal query performance
Optimize and update Conceptual Logical and Physical data models tofoster a new and secure data environment
Assist in establishing best practices for standard naming conventions
Coordinate activities with the EDL team including developers andtesters
Assist in promoting database objects from lower to higher environments
Lead design reviews of data models and relevant metadata to ensureconsistency
Recommend opportunities for the reuse of data models across projects
Consult with Database Administrators regarding the creation ofphysical data schemas referential integrity and the fulfillment of businessrequirements
Collaborate with ETL developers report developers and end users oneffective 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.
REQUIRED SKILLS
Data Architecture 15 Years
AWS Cloud Architecture 10 Years
AWSGlue/Athena/Storage/Lambda/Data Brew/RDS/Redshift DMS 10 Years
Operational Data ModelingSkills 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 multitasking 5 years
DESIRED SKILLS
Mainframe Technologies including Cobol Db2 IMS DB/DC VSAM JCL 5 years
Knowledge of working in Federal State and Local Government 5 year
Employment Type
Full Time
