Experis
Responsibilities:Accountable for defining standards data architecture strategy and roadmap aligned with the Digital Innovation team and Standards business goals.Building effective relationships with business and product partners, translating requirements into clear designs and processes for data production, management, and consumption.Acting as a key stakeholder and advisor in complex strategic initiatives, ensuring alignment across the organization and that design is in accordance with the strategy.Overseeing the governance and high-level design of multiple data models, developing a broad understanding of their relationships and how each fulfills the needs of the organization.Working in close collaboration with systems and solutions architects, engineers, and product partners across the enterprise to provide technical oversight, leadership, and consultation on data relevance, structure, and lifecycle.Actively contributing toward data-related security,compliance, and privacy practices, ensuring they are embedded in the strategy.Setting and advocating standards, principles, and ways of working for the broader Data Architecture community.Building and maintaining appropriate artifacts to support communication and alignment to the strategy.Developing key performance indicators to assure integrity, confidence, and quality of data.Assessing technology and regulatory trends in the wider data landscape, how they may impact opportunities and timing for adoption.
Requirements: Strong understanding of data modeling concepts, including entity-relationship modeling and XML schema design.Proficiency in XML and related standards such as XML Schema (XSD), Document Type Definition (DTD), XPath, and XQuery.Proficiency in using XPath and XQuery to navigate and query XML data.Experience with XML parsing libraries and tools in various programming languages (e.g., Python’s lxml, Java’s JAXB, .NET’s XmlDocument).Experience with designing NoSQL and or XML Database oriented data structures to handles a vast variation of XML schemas.Ability to integrate XML data with other data sources and systems using ETL tools.Foundational knowledge of Enterprise Architecture, Domain Driven Design principles, systems development, application design and information management.Knowledge of industry best practices for XML data modeling and processing.Experience with data architectures and understanding of a broad range of data-oriented technologies and their applicability.Experience with one or more data warehouse platforms (preferably MarkLogic).Understanding of the principles, practices and techniques of Data Engineering for machine learning and AI based systems.Working knowledge of one or more programming languages (e.g., .Net), visualization techniques and analytics tools.
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