Job Summary
This hybrid day shift role is for a seasoned technical lead with deep hands on experience in Azure Data Factory and Databricks guiding complex data engineering initiatives for an international organization. The role focuses on architecting robust data pipelines and analytics solutions mentoring technical teams and collaborating with business stakeholders. Experience in life and annuities insurance is preferred to enhance domain driven design and insight generation across enterprise data plat
Responsibilities
Drive end to end design and implementation of scalable data pipelines using Azure Data Factory and Databricks to support enterprise analytics and reporting needs across the organizationLead technical solutioning for complex data integration scenarios by defining patterns for ingestion transformation and orchestration that ensure reliability performance and maintainabilityCoordinate hybrid model delivery activities by planning onsite and remote work schedules that optimize collaboration with cross functional partners and maintain consistent progress on critical milestonesProvide technical guidance to data engineers and developers by reviewing code design artifacts and deployment approaches to uphold high standards of quality security and operational stabilityCollaborate with business and product stakeholders by translating analytical and reporting requirements into well structured Azure based data solutions that deliver measurable value to customers and internal teamsOptimize Databricks workloads by tuning clusters jobs and queries to improve cost efficiency execution speed and resource utilization while enforcing best practices for workspace organization and governanceImplement robust monitoring logging and alerting for Azure Data Factory and Databricks jobs by leveraging native tools and dashboards to proactively identify issues and reduce downtimeEnsure data quality and consistency across data pipelines by designing validation rules reconciliation checks and error handling strategies that strengthen trust in curated datasets and downstream analyticsCoordinate secure data access and compliance alignment by working with security and risk partners to apply appropriate controls masking and role based permissions across data platformsSupport project planning and estimation activities by providing realistic effort assessments for data engineering tasks enabling accurate timelines and resource allocation for delivery teamsPartner with architecture and infrastructure groups by aligning solutions with enterprise standards reference architectures and cloud governance guidelines to maintain long term sustainabilityContribute to continuous improvement initiatives by capturing lessons learned researching emerging Azure data services and proposing enhancements that increase productivity and innovation across projectsEngage with domain experts in life and annuities insurance when available by shaping data models metrics and analytics that reflect key business processes and improve decision making for policy and claims outcomes
Qualifications
Demonstrate extensive hands on expertise with Azure Data Factory including pipeline development data flow configurations and integration runtime management for complex enterprise workloadsApply strong Databricks knowledge by building performant notebooks jobs and workflows that leverage Spark based processing for batch and near real time data transformation scenariosBring proven experience in designing cloud data architectures that include storage choices compute strategies and integration patterns aligned with organizational standards and performance expectationsUtilize solid data engineering fundamentals such as modeling ETL design optimization and testing to create resilient data solutions that are easy to maintain and extend over timeLeverage any background in life and annuities insurance to interpret business concepts such as policy lifecycle underwriting claims and actuarial analysis when designing data structures and analytics outputsCommunicate effectively with technical and nontechnical partners by explaining solution approaches dependencies and risks in clear language that supports informed decisions and collaborative planningOperate comfortably in a hybrid work environment by using collaboration tools disciplined documentation and regular touchpoints to maintain transparency and alignment across onsite and remote participants
Certifications Required
Azure Data Engineer Associate or equivalent cloud data certification preferred
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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