Enterprise Data Architect

W2 Only

for W2 Candidates

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 12 Years

AWS Cloud Architecture 10 Years

AWSGlue/Athena/Storage/Lambda/Data Brew/RDS/Redshift, DMS 10 Years

Operational Data ModelingSkills 12 Years

Analytical Modeling Skills 12 Years

Data Governance 10 Years

Master Data Management 12 years

Metadata Management 11 Years

Data Cataloging 10 Years

Data Engineering and ETL 10 Years

Data Quality 12 Years

Excellent written and verbal communication skills 10 years

Strong attention to detail 10 years

Ability to write in explanatory and procedural styles for multiple audience 10 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