Java Full Stack Engineer - Data Analytics Location: Glasgow, UK Work Mode: Hybrid (Remote) Job Type: Full-Time / PermanentWe are hiring a Java Full Stack Engineer with strong Data Analytics experience to join a dynamic technology team based in Glasgow. This is a hybrid role, offering the opportunity to work on modern, scalable systems using advanced Java, cloud, and data-driven technologies.Role OverviewThe ideal candidate will have strong hands-on experience in Java Full Stack development, modern frameworks, microservices architecture, and data analytics platforms. You will work closely with engineering, DevOps, and data teams to deliver high-quality, scalable solutions.Mandatory SkillsJava (7-17)Apache KafkaMongoDBSnowflake(If not Snowflake, strong Data Analytics experience is acceptable)Core Technical SkillsProgramming & FrameworksJava, PythonSpring Boot 3.x, Hibernate, JPAMicroservices architectureREST APIs, Spring MVC, Spring CloudApache KafkaDatabases & Data PlatformsMySQL, SQL Server, OracleMongoDB (NoSQL)SnowflakeETL and Data Analytics conceptsDevOps & CloudDocker, Kubernetes (OpenShift)Jenkins, CI/CD pipelinesAzure or AWS (S3 - basic knowledge)Tools & UtilitiesGit, Maven, GradleSonarQube, Checkstyle, SpotlessGitLab / BitbucketSwagger, PostmanJira, ConfluenceGitHub CopilotMonitoring & ReportingDatadog, New RelicSonarQube, Aqua Scan, CheckmarxElasticSearchKey ResponsibilitiesDesign, develop, and maintain scalable full stack applications using Java (Spring Boot) and Python (FastAPI/Django)Build and consume RESTful APIs and microservicesWork with Data Scientists to integrate ML models, predictive analytics, and NLP solutions into production systemsDesign and optimize schemas across SQL, NoSQL, and Snowflake databasesDeploy and manage applications using AWS/Azure, Docker, and KubernetesBuild and maintain CI/CD pipelines ensuring high-quality and secure releasesLeverage GitHub Copilot to enhance development productivityWhy Join?Work on modern data-driven and AI-enabled platformsExposure to cloud, analytics, and ML integrationsHybrid working modelLong-term career growth in a stable full-time role