Job Summary
Architect role for an experienced professional with twelve to sixteen years of background in designing and delivering large scale data and machine learning platforms using Azure Databricks and Azure Machine Learning in media and entertainment domain focused environments. The role uses a hybrid work model in day shift and emphasizes secure scalable and responsible solutions.
Responsibilities
Design robust Azure Databricks based data platforms that support high volume media content workflows and complex analytics needs for global business teams in a hybrid work environmentArchitect end to end Azure Machine Learning solutions that enable advanced prediction models for audience engagement content performance and personalized recommendations in media and entertainment use casesDefine scalable data lake and medallion architecture patterns on Azure that ensure reliable ingestion curation and consumption of structured and unstructured media data assetsCoordinate with product owners and domain experts to translate media and entertainment business goals into practical data and machine learning features and implementation roadmapsGuide engineering teams in implementing secure and cost optimized Azure Databricks clusters jobs and notebooks aligned with organizational governance and compliance standardsEstablish best practices for machine learning lifecycle management including experiment tracking model versioning model retraining and responsible deployment using Azure Machine LearningCollaborate with data engineers data scientists and platform specialists to troubleshoot performance issues and continuously improve data pipelines and model serving pipelinesPrepare detailed solution design documents and architecture diagrams that clearly describe integration points data flows and operational responsibilities for all stakeholdersReview existing media analytics solutions and recommend modernization approaches that leverage Azure Databricks Delta architecture and managed machine learning capabilitiesDefine monitoring strategies and observability standards for batch and streaming data jobs as well as machine learning endpoints to maintain reliable service levels for business critical workloadsDevelop governance guidelines for data quality feature stores and model management that uphold ethical use of data and fair outcomes in media and entertainment decision processesCoordinate security controls such as role based access policies encryption configurations and network isolation to protect sensitive content and usage data within the Azure ecosystemDocument reusable reference architectures patterns and playbooks that accelerate future Azure Databricks and Azure Machine Learning projects and help teams adopt consistent engineering practices
Qualifications
Describe educational background such as degree in computer science data engineering or related field combined with substantial industry experience in data and analytics architectureHighlight mandatory experience in Azure Databricks including cluster design job orchestration notebook development and performance tuning for data heavy media workloadsEmphasize mandatory expertise in Azure Machine Learning for building training evaluating and deploying machine learning models at scale with strong focus on automation and repeatabilityExplain proven experience working in media and entertainment domain including exposure to content supply chains digital distribution streaming analytics and audience measurement scenariosDetail strong proficiency in data engineering concepts such as distributed processing data modeling streaming data pipelines and data lakehouse patterns on Azure cloud platformsMention experience working in hybrid work models and collaborating across distributed teams using modern agile practices documentation standards and transparent communicationState nice to have familiarity with additional Azure services such as Azure Data Factory Azure Synapse and Azure Storage that complement Azure Databricks and Azure Machine Learning in enterprise solutionsDescribe ability to communicate complex technical concepts in clear business oriented language to stakeholders across technology and media business functions
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。
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