Distributed Data Processing Developer
Capgemini
Design distributed data processing applications with Apache Spark and Java, combining scalable architecture, efficient code, and strong SQL skills.This Spark Developer role supports high-performance data solutions from development through production troubleshooting. Responsibilities include reusable Java coding, Spark optimization, data quality, and collaboration with technical and business teams. Required technologies include relational databases, REST APIs, microservices, Git, and CI/CD processes.Key Responsibilities:
Collaborate with teams to gather data solution requirementsDevelop applications using Apache Spark and JavaOptimize jobs for performance and memory managementTroubleshoot production issues and improve application performanceImplement scalable, reliable data processing solutionsRequirements:
At least four years of software development experienceAt least two years developing Spark and Java applicationsStrong SQL and relational database capabilitiesKnowledge of REST APIs and microservices architectureExperience with Git and CI/CD processesUse distributed computing, Spark optimization, Java development, and SQL expertise to deliver dependable large-scale data applications.
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Collaborate with teams to gather data solution requirementsDevelop applications using Apache Spark and JavaOptimize jobs for performance and memory managementTroubleshoot production issues and improve application performanceImplement scalable, reliable data processing solutionsRequirements:
At least four years of software development experienceAt least two years developing Spark and Java applicationsStrong SQL and relational database capabilitiesKnowledge of REST APIs and microservices architectureExperience with Git and CI/CD processesUse distributed computing, Spark optimization, Java development, and SQL expertise to deliver dependable large-scale data applications.
#J-18808-Ljbffr
Vacancy posted 1 hour ago
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