Enterprise Data Architect
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Job Description
Enterprise Data Architect
Trenton, NJ 08625
Hybrid
Both Phone and In Person
Tax Terms: C2C,W2 And 1099
Job Description:
Need a Sr Enterprise Architect focusing for building data architecture Frameworks, Standards, and Data Modeling activities defining Conceptual, Logical, Physical Analytical and Canonical models. 15 yrs Hands on Experience of AWS Architecture required
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.
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.
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 Lambda,AWS 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 Conceptual,Logical, 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 multi-tasking 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 years