Architect

Job Summary

Architect role in a global organization focused on designing and optimizing scalable data and analytics solutions using Azure DevOps Python Databricks SQL Databricks Workflows and PySpark. The role involves hybrid work with day shifts collaborating across teams to create reliable platforms that turn data into actionable insights and support sustainable business outcomes.

Responsibilities

• Design robust end to end data architectures that leverage Databricks SQL Databricks Workflows and PySpark to deliver secure and scalable analytics platforms that support critical business decisions and long term growth outcomes.
• Develop reusable Python and PySpark components that standardize data ingestion transformation and validation patterns so that teams can accelerate delivery while maintaining consistency and quality across projects.
• Implement Azure DevOps based continuous integration and continuous delivery pipelines that automate build test and deployment stages to improve release reliability and reduce operational risk for data products.
• Collaborate with data engineers data analysts and application teams to translate complex functional requirements into pragmatic technical designs that align with enterprise standards and business priorities.
• Optimize Databricks SQL queries and cluster configurations to improve performance manage costs and ensure efficient use of compute resources across multiple data and analytics workloads.
• Define reusable workflow orchestration patterns in Databricks Workflows that coordinate data pipelines quality checks and downstream consumption tasks to ensure predictable and observable operations.
• Establish and document data engineering and coding standards for Python PySpark and SQL so that project teams can follow clear guidelines that support maintainability security and traceability.
• Review solution designs and implementation artifacts to identify architecture risks performance bottlenecks and security gaps and then propose concrete improvements that can be implemented with minimal disruption.
• Guide teams in implementing monitoring logging and alerting across Databricks and Azure resources so that issues can be detected early and resolved before they impact business users and partners.
• Partner with product and business stakeholders to prioritize backlog items that have the highest impact on customer value operational efficiency and responsible use of data across the organization.
• Conduct architecture and design walkthroughs with peer architects and engineers to validate alignment with target reference architectures and to share best practices that raise overall engineering maturity.
• Create clear technical documentation covering solution architecture data flow diagrams security controls and operational procedures so that ongoing support and future enhancements are straightforward and well understood.
• Contribute to innovation initiatives by evaluating new Azure and Databricks features and proposing pilot implementations that can simplify data platforms improve sustainability and enhance societal impact of analytics solutions.

Qualifications

• Require extensive hands on experience designing and implementing data platforms with Databricks SQL Databricks Workflows and PySpark including building scalable batch and near real time data pipelines that support analytics and reporting.
• Require strong proficiency in Python programming for data processing reusable library development and automation with a proven ability to write clean modular and testable code for large scale systems.
• Require demonstrated expertise in Azure DevOps including repository management branching strategies pipeline as code and release automation tailored to data engineering and analytics workloads in hybrid environments.
• Require solid understanding of data modeling performance tuning and query optimization using SQL based technologies so that complex analytical workloads remain responsive and cost efficient.
• Require experience in designing secure data solutions with proper access control data masking and compliance alignment to protect sensitive information and maintain organizational trust.
• Nice to have experience integrating Databricks with broader Azure data services such as data lake storage event based ingestion and downstream visualization platforms to create cohesive end to end solutions.
• Nice to have background working in hybrid work models with distributed teams using collaborative tools and agile practices to coordinate design discussions backlog refinement and delivery planning.
• Nice to have exposure to modern data governance practices metadata management and data quality frameworks to ensure data produced by the platform can be trusted by decision makers and society facing services.

Certifications Required

Preferred Azure Data Engineer Associate or Azure Solutions Architect Expert or Databricks Certified Data Engineer Professional

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。
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