Job Summary
Architect role in a global organization focusing on designing and optimizing cloud native data platforms using Azure and Snowflake technologies. The role requires ten to fourteen years of experience in data engineering and solution architecture working in a hybrid model with day shifts and no travel expectations. The architect will enable secure scalable and reliable data solutions.
Responsibilities
Design robust cloud based data architectures that integrate Azure Functions Azure Data Lake Store Azure Data Factory and Azure Event Hub to support scalable analytics solutions that align with enterprise standards and customer expectations.
Develop end to end data ingestion and transformation workflows using Azure Data Factory and Snowpipe that ensure timely reliable and efficient data movement from diverse operational systems into centralized repositories.
Implement secure and optimized data storage patterns on Azure Data Lake Store that support structured and unstructured data while enabling efficient querying and lifecycle management for analytical workloads.
Create performant Snowflake SQL data models including fact and dimension structures that support complex reporting advanced analytics and self service data consumption by business partners.
Configure and maintain Snowflake Streams and related change data capture patterns that enable near real time data processing and downstream event driven analytics for critical business domains.
Develop and maintain Snowpipe configurations that automate data loading from cloud storage into Snowflake while monitoring performance and optimizing cost and resource utilization.
Set up and manage Azure DevOps pipelines that automate build test and deployment activities for data solutions ensuring consistent repeatable and high quality releases across environments.
Collaborate with cross functional stakeholders to gather requirements translate them into technical designs and ensure that delivered data solutions address current and future analytical needs.
Apply strong data governance security and compliance practices by implementing role based access data masking and audit controls across Azure and Snowflake components.
Optimize query performance and resource usage in Snowflake and Azure data services by tuning configurations reviewing workloads and implementing best practices for cost efficiency.
Provide technical guidance and mentoring to team members on Azure data services Snowflake capabilities and DevOps practices to uplift overall engineering quality and delivery standards.
Document solution architectures data flows operational procedures and support models in a clear and maintainable manner to facilitate smooth operations and future enhancements.
Partner with business and technology teams to identify opportunities where cloud data solutions can improve decision making operational efficiency and positive impact on customers and society.
Qualifications
Demonstrate ten to fourteen years of hands on experience in data engineering and architecture with a strong focus on cloud based platforms and enterprise scale implementations.
Exhibit deep proficiency in Azure Functions Azure Data Factory Azure Data Lake Store and Azure Event Hub by having delivered multiple production grade solutions using these services.
Show advanced skills in Snowflake SQL for designing schemas writing complex queries optimizing performance and troubleshooting production issues in large data environments.
Display practical experience with Snowflake Streams and Snowpipe implementations including configuration monitoring and optimization for near real time or batch data ingestion.
Use Azure DevOps to design and operate CI and CD pipelines for data projects including repository management automated testing and environment deployments.
Apply strong understanding of data governance security and privacy practices across cloud data platforms including role based access encryption and regulatory considerations.
Communicate effectively with technical and non technical stakeholders converting business requirements into scalable and maintainable data solutions that deliver measurable value.
Maintain familiarity with hybrid work practices and remote collaboration tools to support distributed teams while consistently delivering day shift outcomes without travel obligations.
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。
