Key Responsibilities
· Design, develop, and maintain scalable data pipelines using PySpark on AWS.
· Build and orchestrate ETL/ELT workflows using AWS Glue and AWS Step Functions.
· Develop serverless applications and automation using AWS Lambda.
· Write clean, efficient, and maintainable Python/PySpark code following engineering best practices.
· Provision and manage cloud infrastructure using Terraform (Infrastructure as Code).
· Implement and maintain CI/CD pipelines to automate code deployment, testing, and infrastructure changes.
· Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and cost efficiency.
· Collaborate with business stakeholders to deliver data solutions.
· Follow DevOps, security, and coding standards throughout the engagement.
Required Skills
· Strong hands-on experience with PySpark and Python for data engineering.
· Experience developing ETL pipelines using AWS Glue.
· Proficiency with AWS Step Functions for workflow orchestration.
· Experience building serverless solutions using AWS Lambda.
· Hands-on experience with Terraform for Infrastructure as Code (IaC).
· Experience implementing CI/CD pipelines using tools such as GitLab, GitHub Actions, Jenkins, or similar.
· Good understanding of AWS services, data lakes, IAM, S3, CloudWatch, and monitoring.
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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