AIA Coimbatore
Experience : 6 to 9 years
Job Summary
Contribute as a senior developer specializing in PySpark and Palantir Foundry to build scalable data pipelines and analytical solutions within a global enterprise environment. Collaborate with cross functional teams in a hybrid work setup to transform complex business requirements into reliable data products that improve decision making and operational efficiency.
Responsibilities
- Design robust PySpark data pipelines that reliably process large scale structured and unstructured datasets to enable accurate reporting and analytics for business stakeholders.
- Develop optimized transformations in PySpark that improve runtime performance and resource utilization while maintaining high standards of data quality and consistency.
- Implement modular data workflows in Palantir Foundry that integrate diverse enterprise data sources and provide curated datasets for downstream applications.
- Configure and manage datasets transformations and schedules in Palantir Foundry to ensure that critical data assets remain fresh traceable and well documented.
- Collaborate with product owners data analysts and other developers to translate business requirements into clear technical specifications and reusable data components.
- Conduct detailed code reviews for PySpark and Foundry transformation logic to uphold coding standards improve maintainability and reduce production issues.
- Troubleshoot complex data pipeline incidents by performing root cause analysis and implementing sustainable fixes that prevent recurrence and protect service reliability.
- Optimize data models and query patterns so that analytical and operational dashboards perform efficiently and deliver timely insights to decision makers.
- Document data lineage business rules and transformation logic in a clear and accessible manner so that teams across the organization can confidently reuse shared data assets.
- Partner with platform and infrastructure teams to ensure that Spark cluster configurations job schedules and resource allocations align with performance and cost objectives.
- Apply secure coding and data handling practices to safeguard sensitive information and comply with internal policies and external regulatory expectations.
- Provide mentoring and guidance to less experienced developers on PySpark patterns testing approaches and best practices for building reliable data solutions.
- Engage in continuous improvement activities by evaluating new features in Palantir Foundry and Spark technology ecosystems to enhance the resilience and scalability of existing solutions.
- Coordinate with testing teams to define test data strategies validation rules and automated checks that verify correctness of complex data transformations before production deployment.
- Communicate progress risks and technical constraints clearly to project stakeholders so that delivery timelines and scope can be managed effectively.
- Partner with business teams to identify opportunities where advanced data engineering on Spark and Foundry can streamline processes and create measurable value for customers and communities.
- Ensure that hybrid working practices are effective by using collaboration tools regular check ins and documented workflows that support both in office and remote team members.
- Align daily development activities with the organization mission by focusing on data capabilities that drive better services improved sustainability and responsible use of technology.
Qualifications
- Demonstrate six to eight years of hands on experience in designing and implementing data engineering solutions using PySpark in large scale enterprise environments.
- Exhibit strong proficiency in Palantir Foundry including building transformations managing datasets configuring schedules and integrating with upstream and downstream systems.
- Apply solid understanding of distributed data processing concepts such as partitioning caching and shuffle optimization to tune PySpark jobs for performance.
- Use practical knowledge of SQL and data modeling to design schemas joins and aggregations that support both analytics and operational use cases with high data quality.
- Show proficiency in version control and collaborative development practices so that changes to PySpark and Foundry assets are traceable reviewable and reversible.
- Employ experience with testing frameworks and data validation techniques to establish automated checks that secure reliability of production data pipelines.
- Display excellent communication and collaboration skills that enable effective work with cross functional teams in a hybrid work environment without requiring frequent travel.
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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