Enterprise Data Architect - Remote

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    "datePosted": "2024-06-06T19:57:04.630Z",
    "description": "<h2>Overview</h2>\n<p>Location:  Remote - must be available to work EST hours</p>\n<p>Job Type: Full Time / Contract </p>\n<p>Work Authorization: No Sponsorship</p>\n<p> </p>\n<p>The A.C.Coy Company has an immediate need for an Enterprise Data Architect.  Ideal candidates must have 10+ years of experience as a Data Architect.</p>\n<h2>Responsibilities</h2>\n<ul>\n <li>Lead the design, develop and implement data models for enterprise-level applications and systems.architected in the following layers: conceptual, logical, business area, and application</li>\n <li>Create short-term tactical solutions to achieve long-term objectives and an overall data management roadmap</li>\n <li>Establish methods, tools, and procedures for tracking data quality, completeness, redundancy, and improvement</li>\n <li>Propose and collaborate on plans for security, backup, disaster recovery, business continuity, and archiving within the domain architect area</li>\n <li>Identify, establish, publish, and communicate the data principles, standards, frameworks, structures, technology components, interfaces, patterns, methodologies, and best practices</li>\n <li>Conduct data capacity/workload planning, life cycle, duration, usage requirements, feasibility studies, and other tasks</li>\n <li>Develop and promote data management methodologies and standards</li>\n <li>Develop and implement key components as needed to create testing criteria to guarantee the fidelity and performance of data architecture</li>\n <li>Collaborate with Architecture & Governance, Integration, Infrastructure, Security, Data Privacy, and other groups to establish and champion the adoption of a modern data architecture practice</li>\n <li>Oversee the development team by monitoring and reviewing the quality, performance, security, and scalability of solutions, addressing any technical issues to ensure compliance with requirements, standards, and policies</li>\n <li>Work with the compliance team to ensure that data strategies and architectures are in regulatory compliance</li>\n <li>Integrates relevant security and compliance standards into all data architectural designs to build a robust framework</li>\n <li>Advocates for security and risk management practices at every architectural touchpoint to protect data from unauthorized access and maintain privacy in compliance with regulations like GDPR, HIPAA, and CCPA</li>\n <li>Coordinate and manage FEAT work-intake tasks and associated strategies to ensure proper alignment and successful implementation by leveraging architectural consulting expertise, direction, and support</li>\n <li>Develop comprehensive plans for integrating new systems with existing ones to establish baseline architecture and system requirements, ensuring seamless interoperation of different systems and promoting reusability </li>\n <li>Maintain and develop a thorough architecture (domain architect area) blueprint, considering business needs, constraints, and industry standards within the domain architect area</li>\n <li>Oversee the mapping of data sources, data movement, interfaces, and analytics, to ensure data quality</li>\n <li>Identify opportunities for data reuse, migration, or retirement, and resolve data issues related to data systems integration, compatibility, and multi-platform integration</li>\n</ul>\n<h2>Qualifications</h2>\n<p>Education:</p>\n<ul>\n <li>Degree in computer science, information systems, or computer engineering</li>\n</ul>\n<p>Certification:</p>\n<ul>\n <li>TOGAF (The Open Group Architecture Framework) - Preferred</li>\n</ul>\n<p>Requirements:</p>\n<ul>\n <li>Data or information architect - 10+ years</li>\n <li>Hands-on experience with data architecting, data mining, large-scale data modeling, business requirements gathering/analysis, entity relationship planning, database design, reporting structures -10+ years</li>\n <li>Direct experience in implementing enterprise data management processes, procedures, and decision support</li>\n <li>Strong understanding of AI foundational principles, governance, and how data needs to be ready for AI</li>\n <li>Strong familiarity with metadata management and associated processes, as well as managing data and metadata migration</li>\n <li>Extensive hands-on experience with enterprise repository tools, data modeling, mapping, profiling, and repository creation, as well as data and information system life cycle methodologies</li>\n <li>Knowledge of applicable data privacy practices and laws</li>\n <li>Proven experience in architecting and implementing Business Intelligence and Data Warehouse platforms, Master Data Management, data integration, and OLTP database solutions</li>\n <li>A comprehensive understanding of data warehousing and data transformation (extract, transform, and load) processes and the supporting technologies, such as Azure Data Factory, Data Lake, and other analytics products</li>\n <li>Experience working with Data in AI systems - Preferred</li>\n</ul>",
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