Job Summary
Sr Developer with 6 to 10 years of experience will design and optimize data solutions using LakeHouse Spark Job Definition OneLake SQL and PySpark while working in a hybrid day shift model and collaborating with cross functional teams to deliver reliable analytics that support retail banking focused initiatives and strategic decision making across the organization
Responsibilities
Design advanced data processing solutions on LakeHouse platforms that enable reliable analytics and reporting for critical business initiatives across hybrid environmentsDevelop scalable Spark Job Definition pipelines that process large data volumes efficiently while maintaining accuracy and consistency for downstream consumersBuild and optimize PySpark jobs that transform raw data into curated data sets supporting complex analytical models and operational dashboards for internal stakeholdersWrite high quality SQL queries and stored procedures that ensure robust data extraction transformation and loading while adhering to performance and security standardsImplement data models within OneLake that unify structured and semi structured data sources to provide a single trusted view for analytics and data productsCollaborate with data engineers architects and analysts to translate business requirements into technical solutions that align with enterprise data strategiesOptimize data pipelines for performance reliability and cost efficiency by tuning Spark configurations query logic and resource utilization across environmentsImplement data quality checks validation rules and monitoring processes that prevent data issues and ensure trustworthy insights for decision makersDocument technical designs data flows and operational procedures clearly so that solutions are easy to maintain enhance and troubleshoot by the wider teamSupport production deployments by analyzing issues performing impact assessments and implementing stable fixes that minimize disruption to business operationsParticipate in code reviews knowledge sharing sessions and continuous improvement activities that uplift engineering standards and foster a culture of technical excellencePartner with business teams in domains such as retail banking to understand use cases and ensure data solutions deliver measurable value and positive societal impactAdapt effectively to the hybrid work model by collaborating through digital tools coordinating with onsite and remote colleagues and maintaining clear communication
Qualifications
Demonstrate strong hands on expertise in LakeHouse architectures with a proven track record of delivering scalable and secure data solutions in enterprise settingsExhibit advanced skills in Spark Job Definition and PySpark including experience with performance optimization fault tolerance and batch or streaming workloadsShow proficiency in SQL with the ability to design complex queries optimize execution plans and implement robust data transformations in production environmentsApply practical experience with OneLake or similar unified data platforms to consolidate disparate sources and support analytics self service and governance requirementsBring solid experience in data engineering or development roles with six to ten years of progressive responsibility in modern data platforms and toolsUtilize knowledge of retail banking or financial services as a nice to have capability to design solutions that align with domain specific data patterns and regulatory needsCommunicate clearly with technical and non technical partners and contribute to a collaborative culture that supports ethical data use and better outcomes for customers and society
Certifications Required
Preferred certifications include Databricks Data Engineer Associate or Azure Data Engineer Associate or equivalent cloud data engineering credentials
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
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