Enterprise Data Architect - AWS - Trenton, NJ

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.

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

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 andverbal communication skills 15 years

Strong attention to detail 15 years

Ability to write inexplanatory and procedural styles for multiple audience 15 years

Skilled at prioritizationand multi-tasking 5 years

DESIRED SKILLS

Mainframe Technologiesincluding Cobol, Db2, IMS DB/DC, VSAM, JCL 5 years

Knowledge of working inFederal, State and Local Government 5 years

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.