Job Summary
This hybrid role is for an experienced developer with strong skills in Python Databricks SQL Databricks Workflows and PySpark focused on building scalable data solutions and analytics pipelines. The developer will design implement and optimize data processing workflows that support business insights improve operational efficiency and contribute to impactful data driven products for global stakeholders.
Responsibilities
- Design robust data processing pipelines using Python and PySpark in Databricks to transform complex data into reliable curated datasets that enable advanced analytics and reporting across the organization.
- Develop optimized Databricks SQL queries to support performant dashboards and analytical workloads ensuring data consumers can access trusted information with minimal latency and high reliability.
- Configure and manage Databricks Workflows to orchestrate end to end data jobs ensuring timely execution effective dependency handling and consistent delivery of data assets to downstream applications.
- Implement reusable modular code components and libraries in Python that standardize data transformations and business logic leading to faster development cycles and improved maintainability.
- Collaborate closely with data engineers analysts and product teams in a hybrid work model to gather requirements validate solutions and align data products with strategic business objectives.
- Optimize PySpark jobs for performance and cost efficiency by tuning configurations managing partitioning strategies and leveraging best practices for large scale distributed processing.
- Ensure data quality and reliability by implementing validation checks error handling mechanisms and logging standards that reduce data issues and support faster troubleshooting.
- Conduct thorough unit testing integration testing and performance benchmarking for Databricks workflows to ensure stable releases and minimize disruptions to data consumers.
- Document datasets workflows and code logic in clear technical artifacts so that other team members can understand reuse and extend solutions effectively over time.
- Provide support for day shift operations by monitoring data workflows resolving production issues and proactively identifying opportunities to improve data reliability without requiring travel.
- Engage in continuous improvement by evaluating new Databricks features Python libraries and data engineering practices that can enhance scalability security and usability of data platforms.
- Collaborate with cloud and security teams to ensure that all Databricks development adheres to organizational policies governance standards and compliance requirements benefiting stakeholders and society through responsible data use.
- Participate in code reviews and knowledge sharing sessions in the hybrid work environment to promote high quality development practices and foster a culture of continuous learning and innovation.
Qualifications
- Demonstrate strong proficiency in Python programming with hands on experience in writing efficient modular and testable code for data engineering and analytics use cases.
- Exhibit solid experience in authoring and optimizing Databricks SQL queries for complex joins aggregations and analytical functions that support business reporting and data exploration.
- Show practical expertise in building scheduling and managing Databricks Workflows including job orchestration parameterization and monitoring to support dependable data operations.
- Apply deep understanding of PySpark fundamentals including RDDs DataFrames and Spark SQL along with performance tuning techniques suitable for large scale distributed data processing.
- Bring relevant experience of four to seven years in data engineering or analytics focused development roles working on hybrid work models and collaborating with cross functional teams.
- Demonstrate familiarity with version control practices testing frameworks and CI CD concepts that support reliable code deployment in modern data platforms.
- Display strong communication and problem solving skills that enable effective collaboration with technical and nontechnical partners while focusing on delivering impactful data solutions.
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。
