Job Summary
This hybrid role requires an experienced architect with deep expertise in data architecture data virtualization data catalog management DevOps practices SQL and data integration. The architect will design scalable data ecosystems enable secure and compliant data access and support business decision making through reliable data platforms aligned with enterprise strategy.
Responsibilities
Design and maintain a comprehensive enterprise data architecture that aligns with organizational strategy and supports long term scalability and resilienceDevelop robust data models and standards that ensure consistency accuracy and usability of data across analytical and operational platformsImplement data virtualization solutions that provide unified access to diverse data sources while minimizing data movement and duplicationCreate efficient SQL based solutions that optimize query performance support complex analytics and improve time to insight for business teamsDefine and implement data integration patterns that support batch and real time data flows while maintaining reliability and data qualityEstablish DevOps practices for data platforms that automate deployment testing and monitoring to improve delivery speed and platform stabilityCollaborate with cross functional stakeholders to translate business requirements into practical data solutions that deliver measurable valueDevelop and manage data catalog structures that enhance data discovery stewardship and trust through clear definitions and lineageImplement data governance and security controls that protect sensitive information and ensure compliance with regulatory and organizational standardsOptimize data pipelines and platform resources to balance performance cost efficiency and sustainability objectives for the organizationGuide teams in adopting best practices for data design coding standards and documentation to improve maintainability and knowledge sharingPerform impact analysis for changes to data structures and integration flows to reduce risk and ensure continuity of critical business processesMentor peers on modern data architecture patterns to build organizational capability and support a culture of continuous improvement
Qualifications
Possess extensive experience in designing enterprise data architectures that support analytics platforms data warehouses and data lakesDemonstrate strong hands on expertise in SQL including query optimization data modeling and performance tuning in complex environmentsShow proven experience with data virtualization tools and concepts enabling unified access to heterogeneous data sourcesBring solid background in data integration technologies covering batch streaming and API based data movement with focus on reliabilityExhibit practical experience with DevOps or data ops practices including automation of deployment testing and monitoring of data solutionsHave experience implementing and managing data catalog solutions that support metadata management data lineage and governance processesUnderstand data governance privacy and security principles and apply them to design compliant and secure data platformsDisplay strong communication and collaboration skills to work effectively with technical and non technical stakeholders in a hybrid work model
Certifications Required
Preferred certifications include data engineering or architecture credentials such as Azure Data Engineer Associate or Google Professional Data Engineer
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
