Job Summary
This hybrid day shift role seeks a seasoned Technical Lead with eight to twelve years of experience in designing and optimizing data solutions using Apache Synapse Synapse Pipelines and Azure Synapse. The role focuses on delivering resilient analytics platforms for media and entertainment initiatives ensuring scalable data flows that support audience insights content performance analysis and business growth.
Responsibilities
- Drive end to end design of data integration solutions using Apache Synapse and Synapse Pipelines to support complex analytics needs for media and entertainment programs
- Develop robust Azure Synapse architectures that efficiently process large scale content consumption data enabling timely insights for programming and marketing teams
- Implement optimized data models tailored to media usage patterns that enhance reporting accuracy for streaming performance ratings and audience engagement metrics
- Coordinate hybrid work activities and ensure continuous collaboration between onsite and remote team members to maintain predictable delivery of analytics features
- Configure and maintain secure data pipelines that respect regional regulations for content and user data ensuring compliant insights for global media strategies
- Analyze existing data workflows in media and entertainment systems and recommend improvements that reduce latency and accelerate delivery of dashboards for decision makers
- Optimize extraction and transformation processes from diverse media sources such as content catalogs viewing logs and advertising platforms to provide unified analytics views
- Guide resolution of technical issues related to Apache Synapse or Azure Synapse environments ensuring minimal disruption to daily reporting and campaign analysis
- Collaborate with data scientists and business analysts to convert audience behavior hypotheses into production grade pipelines that support experimentation and continuous optimization
- Document solution designs operational procedures and hybrid work practices in a clear and accessible manner to support maintainability and onboarding of new team members
- Monitor performance of Synapse Pipelines and storage layers and implement tuning strategies that improve responsiveness of interactive analytics tools used by content stakeholders
- Align technical implementations with sustainability and efficiency goals by designing resource conscious data processes that minimize compute waste while meeting platform performance expectations
- Support day shift release and validation activities by coordinating deployments testing and incident follow up which helps media operations run smoothly without overtime disruptions
Qualifications
- Demonstrate substantial hands on expertise in Apache Synapse configuration pipeline orchestration and troubleshooting for data driven media analytics
- Show advanced proficiency in designing and operating Synapse Pipelines including complex transformations and scheduling logic aligned with entertainment content life cycles
- Apply deep experience with Azure Synapse services such as dedicated SQL pools serverless querying and security controls to build enterprise grade analytics platforms
- Bring proven domain experience in media and entertainment with practical exposure to content distribution audience measurement and advertising data ecosystems
- Use strong data engineering skills in areas such as SQL performance tuning data warehousing and batch or near real time processing to support demanding analytics workloads
- Exhibit solid understanding of hybrid work models and modern collaboration practices ensuring consistent communication and efficient delivery in mixed location teams
- Display effective problem solving and analytical abilities that enable quick diagnosis of pipeline failures data quality issues and performance bottlenecks in Synapse workloads
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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