Enterprise Data Architect

The Sr Enterprise Data Architect will focus on:

AWS Cloud DataArchitecture.

Building Data Architecture Frameworks,

Data pipeline frameworks,

Standards, and Data Modeling Activities for UI Mod

All underlying systems, data owners, databases, andapplications working together with the Sr Data Management Lead and the Officeof the CIO in defining the Conceptual, Logical, Physical Analytical andcanonical models. This work stream will focus on several systems in scope.

The DA will analyze the data needs of the systems anddatabases and uses skills in coding to maintain secure databases. They thencollect and organize the data obtained into structured data models.Additionally, using mathematical and statistical theory methodstheypresentfindingstomanagementwhich are then used to improve various initiatives within the NJDOL systems.

Will meet with business teams and determine the best methodstogathertheinformation required.

The Enterprise Data Architect must:

Research and properly evaluate resources ofi nformationt o determine possible limitationsi in reliability or usability

Apply sampling techniques to effectively determine and define ideal categories to be questioned

Compare anda nalyze provided statistical information to identify patterns,relationships, and problems

-Define and utilize statistical methods to solve industry-specific problems and engineer data structures Prepare detailed reports for management and otherdepartments by analyzing and interpreting data.

KNOWLEDGE AND EXPERIENCE

15+yearsofexperience in Business/ITworking asaDataArchitect,DataModeler, DataAnalystand/or Business ProcessSupportAssociate

Expertise in Data Modeling, SolutionArchitecture, Master Data Management (MDM),Business Process Analysis/Engineering, Business Requirements Gathering andSystemsAnalysis in State, Local Government and Public SectorDomains

Expertise in one or more DataModelingTools

Experienced in working with different Software Development Methodologies.

-Proficient in, NoSQL, Relational,MDM and Canonical DataModeling.

Extensive Knowledge of Data Management Principles

-Extensive Knowledge of Master Data Management Principles

-Knowledge of Data Governance Concepts

Knowledge of Data Engineering Methodologies

-Knowledge of Data Engineering

DUTIES and RESPONSIBILITIES

ConductCurrentStateAssessmentofDataSystems

DefineSystem of Record and Data Dictionary for Data Systems DevelopEnterpriseConceptual,LogicalandPhysicalDataModels

Creates and buildsConceptual, Logical and Physical Models

FacilitatesBusinessSessionsandvalidates businesstaxonomy andusecasesaligned to data models

Provideinitialdesignsolutionfor coredatamodelaswell as for additional upcoming data sources and required models supporting

SupportProject Needs todesign ConceptualLogical and Physical Models toModernization Efforts

Define theNJDOL architecture fromConceptual,Logical toPhysical layers. Provide solution expertise to cross functionaldelivery teams

Providearchitecturethoughtleadershipandactivelyparticipateinthedesign, implementation, and roll-out efforts.

DevelopandmaintainConceptual,logicalandphysicaldatamodelsusingbestpracticesandDOLstandardstoensurehighdataquality,reduceddataredundancy, and good query performance.

Reverseand forward engineer data models in Erwin or other Data ModelingTools

Optimizeand update Conceptual, logical and physical data models to support new andexisting projects and ensure business users are working ina clean safedata environment.

Assistin the creation of best practices for standard naming conventions and codingpractices to ensure consistency of data models.

Coordinateactivities with the rest of the EDL team including developers and testers;Assistinpromotingdatabaseobjectsfromlowertohigherenvironments.

Leaddesign reviews of data models and other relevant metadata to ensureconsistency, quality, accuracy and integrity.

Recommendopportunitiesforreuseofdatamodelsinnewprojects.

Consultwith Database Administrators concerning the creation of physical data schemafrom the logical model by making recommendations, designing referentialintegrity, and ensuring business requirements are satisfied.

Consult with ETL developers,report developers, end users concerning how to use the database as designed and how to navigate efficiently within the database.

Guide System Analysts, Engineers, Programmers and others on project limitations and capabilities,performance requirementsandinterfaces,andsystem integration challenges and solutions.

Mentor DOL teammembers on all aspects of DataModeling.

REQUIREDSKILLS

DataArchitecture 15 Years

AWSCloudArchitecture15Years

OperationalDataModelingSkills15Years

AnalyticalModeling Skills 15 Years

CanonicalModeling 10 Years

InformationGovernance 10Years

MasterDataManagement15years

MetadataManagement 10 Years

DataCataloging 15 Years

DataEngineeringandETL15Years

DataQuality 15 Years

Excellentwrittenandverbalcommunicationskills,5years

Proficiencyin MS Office, 5 years

Strongattentiontodetail,5years

Abilitytowriteinexplanatoryandproceduralstylesformultipleaudiences,5years

Skilledatprioritizationandmulti-tasking,5years

MainframeTechnologiesincludingCobol,Db2,IMS DB/DC, VSAM, JCL and other middleware tools

KnowledgeofworkinginFederal,StateandLocalGovernment

Data Architecture
AWS Cloud Architecture
Operational Data Modeling Skills
Analytical Modeling Skills
Canonical Modeling
Information Governance
Metadata Management
Data Cataloging
Data Engineering and ETL
Proficiency in MS Office
Experiene documenting in an explanatory and procedural style for multiple audiences
Mainframe Technologies including Cobol, Db2, IMS DB/DC, VSAM, JCL and other middleware tools
Knowledge of working in Federal, State and Local Government
Leadership experience with experience managing and mentoring small teams
Bachelors Degree

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