Data Engineer
Primary Skills
Python, Java, Kotlin — Proficient in writing clean, efficient, and maintainable code using modern programming languages.
Apache Spark, Hadoop, Kafka — Experience with Spark for large‑scale data processing and distributed data engineering environments.
Apache Hive — Knowledge of Hive for building and maintaining data warehousing solutions.
Apache Airflow — Skilled in orchestrating complex data workflows using Airflow.
SQL Server — Experience with SQL Server for database management and querying.
Software Testing Principles — Ability to design unit and integration tests (PyTest, JUnit) ensuring data accuracy and reliability across pipeline stages.
Docker & Kubernetes — Hands‑on experience deploying and managing data services in containerized environments.
CI/CD Tools — Familiarity with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
Role Overview
We are seeking a highly skilled Data Engineer to design, build, and maintain scalable data infrastructure and pipelines. The ideal candidate has strong experience with distributed systems, modern data processing frameworks, and cloud‑native deployment practices.
Key Responsibilities
Pipeline Development — Design, build, and maintain scalable data pipelines across distributed systems.
Data Governance — Implement and manage frameworks ensuring data quality, security, and compliance.
Performance Optimization — Optimize and troubleshoot data processing jobs for performance and reliability.
Testing Data Workflows — Apply unit and integration testing to validate data workflows and transformations.
Data Warehousing — Develop and maintain data warehousing solutions using Apache Hive.
Workflow Orchestration — Orchestrate data workflows using Apache Airflow.
Database Management — Manage and query databases using SQL Server.
Cross‑functional Collaboration — Work closely with data scientists and analysts to deliver data solutions.
Containerized Deployment — Use Docker and Kubernetes to deploy and manage data services.
CI/CD Automation — Implement CI/CD pipelines for automated testing, deployment, and monitoring.
Data Quality — Ensure data integrity and reliability across all pipelines.
Qualifications
Data Engineering Experience — Proven experience as a Data Engineer or similar role.
Programming Skills — Strong programming skills in Python, Kotlin, or Java.
Distributed Systems — Hands‑on experience with Apache Spark, Apache Hive, Apache Airflow, and SQL Server.
Cloud Platforms — Familiarity with AWS, GCP, or Azure is a plus.
Problem-solving — Excellent analytical skills and attention to detail.
Teamwork — Strong communication and collaboration abilities.
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。
