Job Summary
Serve as a senior developer specializing in Spark in Scala and Azure Synapse to design build and optimize large scale data engineering solutions that power analytics and digital products. Collaborate in a hybrid work model with cross functional teams to deliver secure reliable and observable pipelines while leveraging Azure DevOps and cloud native services to support business value including media domain scenarios.
Responsibilities
- Design scalable batch and streaming data solutions using Spark in Scala and PySpark to support complex analytical workloads and reusable data products for enterprise stakeholders in a hybrid work environment.
- Develop robust Synapse Pipelines that orchestrate ingestion transformation and publishing of structured and semi structured data from diverse sources into optimized analytical data stores.
- Implement Structured Streaming jobs that process near real time data feeds to enable event driven analytics and timely business insights while maintaining reliability and consistency.
- Configure and optimize Azure Synapse Spark Pool and Serverless SQL Pool to deliver cost efficient query performance and responsive data exploration capabilities for data consumers.
- Write efficient SQL and Python code that adheres to coding standards while implementing reusable data transformation logic and ensuring maintainable modular solutions.
- Use Azure CLI and Azure PowerShell to automate environment provisioning configuration changes and deployment tasks that improve consistency and reduce manual effort.
- Set up and manage Azure Event Hub integrations that capture streaming events and route them into Synapse based processing pipelines with robust error handling and observability.
- Configure Azure Monitor alerts metrics and logs that track pipeline health performance and failures to support proactive detection and quick resolution of production issues.
- Implement secure secrets and credential management practices using Azure Key Vault to protect sensitive data while enabling safe automation and continuous delivery workflows.
- Use Azure DevOps to design and maintain continuous integration and continuous delivery pipelines that enforce quality gates testing and automated deployment of data solutions.
- Collaborate with architects data modelers and product partners to translate complex business requirements including media domain needs into scalable technical designs and implementation tasks.
- Document data flows transformation logic operational runbooks and support guidelines that help teams understand operate and extend the implemented solutions over time.
- Provide technical guidance and code reviews for peers by sharing best practices in Spark optimization Synapse development security and monitoring to uplift overall team capability.
- Drive continuous improvement initiatives that enhance data reliability performance and developer productivity by introducing new patterns tools and process refinements aligned with organizational goals.
Qualifications
- Possess eight to twelve years of professional experience in data engineering or software development with a primary focus on cloud based big data platforms and large scale analytics solutions.
- Demonstrate deep hands on expertise in Spark in Scala and PySpark including performance tuning partitioning strategies job optimization and troubleshooting of distributed processing workloads.
- Have strong practical experience building complex Synapse Pipelines and notebooks that integrate multiple Azure services and implement end to end data ingestion and transformation processes.
- Exhibit proficiency with Azure Synapse Spark Pool and Serverless SQL Pool including workspace configuration resource management and query optimization for analytical use cases.
- Show advanced skills in SQL and Python applied to data transformation data quality enforcement and analytical dataset preparation in large enterprise environments.
- Bring practical experience with Azure CLI and Azure PowerShell scripting to automate operational tasks infrastructure configuration and deployment of repeatable environments.
- Demonstrate familiarity with Azure Event Hub Structured Streaming and related technologies for implementing near real time and event driven data solutions.
- Show working knowledge of Azure Monitor and related observability tools for setting up dashboards alerts and diagnostics that support production grade monitoring of pipelines.
- Have solid experience with Azure DevOps including repositories pipelines and artifacts to implement continuous integration and continuous delivery for data projects.
- Demonstrate strong understanding of security practices using Azure Key Vault role based access controls and encryption to protect data and credentials across environments.
- Bring domain exposure in media or content centric industries where audience analytics streaming telemetry or digital engagement data are central to business decisions considered a plus.
- Communicate clearly with cross functional teams manage work in a hybrid model and adapt to evolving priorities while maintaining focus on quality reliability and business outcomes.
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。
