Enterprise Data Architect

Enterprise Data Architect is responsible for designing the blueprint for client data management framework. Collaborate with client 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 client 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 Technologies including Cobol, Db2, IMS DB / DC, VSAM, JCL 5 years

Knowledge of working in Federal, State and Local Government 5 years