Job Summary
The Architect role involves designing and implementing scalable data solutions using advanced technologies like MS Data Fabric Power BISpark OneLake SQL PySpark and Have hands- on Experience in Power BI. The candidate will work in a hybrid model collaborating with cross-functional teams to deliver high-quality data architectures that drive business insights and innovation.
Key Responsibilities: Data Engineer
- Pipeline Development: Design, develop, and maintain robust, scalable ETL/ELT data pipelines using Azure Data Factory (ADF) and Azure Databricks.
- Data Transformation: Utilize PySpark and SparkSQL to perform complex data transformations, cleaning, and aggregation.
- Azure Data Lake Management: Work with Azure Data Lake Storage (ADLS) Gen2 and Azure Blob Storage for efficient data handling.
- Data Modeling: Create and optimize data models (conceptual/logical/physical) for Lakehouse architecture (Medallion: Bronze, Silver, Gold).
- Optimization: Perform advanced performance tuning for PySpark jobs and ADF pipelines to ensure reliability and cost efficiency.
- CI/CD & DevOps: Implement CI/CD pipelines for data engineering code using Git, Azure DevOps, or GitHub Actions.
- Collaboration: Work with stakeholders, data scientists, and analysts to translate business requirements into technical solutions
Required Skills: Microsoft Fabric, ADF, Azure Databricks, PySpark, Python, ADLS, SQL, ADO
Certifications Required
Certified Spark Developer Python Data Engineering Certification SQL Database Certification MS Power BI
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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