Job Summary
This hybrid role seeks a senior developer with six to eight years of experience specializing in Databricks SQL Databricks Workflows and PySpark to build and optimize data solutions for life and annuities insurance. The role focuses on scalable pipelines reliable analytics and insight delivery that improve policyholder outcomes and support responsible business decisions.
Responsibilities
Design build and optimize Databricks SQL queries that support complex life and annuities insurance reporting and analytics needs while ensuring accuracy and performanceDevelop robust PySpark based data pipelines that process large insurance datasets efficiently and reliably for downstream actuarial and operational useConfigure and maintain Databricks Workflows that orchestrate end to end data processing and analytics tasks across hybrid environments with predictable executionImplement data quality checks and validation rules tailored to life and annuities products so that policy claim and premium data remains consistent and trustedCollaborate with business analysts and actuaries to translate life and annuities requirements into scalable Databricks solutions that enable data driven decisionsOptimize storage formats partitioning strategies and cluster configurations in Databricks to balance cost performance and reliability for large insurance workloadsCreate clear technical documentation that explains data models transformation logic and workflow behavior in language that is understandable across technology and insurance teamsSupport day to day production operations by investigating incidents resolving data issues and implementing preventive improvements that reduce recurring problemsApply secure coding and data handling practices so that sensitive insurance data is protected in line with enterprise governance and regulatory expectationsCoordinate with hybrid infrastructure and platform teams to ensure Databricks environments connectivity and dependencies are stable for day shift operationsParticipate in sprint activities by estimating effort planning tasks and delivering high quality development outcomes aligned with agreed timelinesEngage with testing teams to define test data scenarios and acceptance criteria that reflect real life and annuities processes and edge casesContribute to continuous improvement by identifying opportunities to streamline workflows reduce manual steps and enhance analytics capabilities for business stakeholders
Qualifications
Possess professional experience of six to eight years in data engineering or development roles with a strong focus on Databricks SQL and PySpark within enterprise settingsDemonstrate hands on expertise in configuring and managing Databricks Workflows for complex multi step data and analytics processes in a hybrid work modelShow deep domain understanding of life and annuities insurance concepts including policy lifecycle premiums claims reserves and related data structuresExhibit strong proficiency in writing efficient PySpark code tuning transformations and handling large scale structured and semi structured datasetsBring practical knowledge of relational databases data warehousing and dimensional modeling techniques that support insurance reporting and analyticsDisplay familiarity with data governance concepts such as data lineage metadata management and access control in regulated industries like insuranceCommunicate clearly with cross functional teams documenting solutions and explaining technical decisions in terms that align with business outcomes
Certifications Required
Preferred certifications include Databricks Data Engineer Associate and relevant insurance or actuarial domain certifications.
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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