Java：47,629 個職缺
瀏覽與 Java 相關的開放職缺。
Senior AI Engineer
Senior AI Engineer at Adaptiq building agentic AI capabilities for a maritime intelligence platform that fuses geospatial data into a digital twin for commercial and government use. Day-to-day work spans LLM/RAG system design, autonomous agent development, Python backend services, and production AI deployment on AWS/Kubernetes.
Solution Engineer
Designs and operates production-grade data pipelines and data products on AWS and Snowflake for a global investment management firm, owning architecture through deployment while using AI-assisted engineering as a daily practice.
SDET QA инженер (Java auto)
QA automation engineer at the Bank of Russia designing and developing automated test scripts in Java for web, desktop, and server applications. Uses Selenium/Selenide/Selenoid/TestNG/JUnit on a Java 17 + Spring Boot stack, covering functional, integration, regression, and load testing.
Enterprise Architect, Professional Services, Google Cloud
Principal Enterprise Architect at Google Cloud Professional Services who bridges business strategy and engineering, advising executive stakeholders and designing cloud-native architectures with AI and agentic workflows.
Business Analyst
Business Analyst on a product team adapting a CRM platform for insurance clients—gathering requirements, writing documentation (user stories, BPMN/UML diagrams, technical specs), and bridging product owners with Java developers and QA. Uses Jira, Confluence, Miro, Figma, and Postman.
Junior Java Developer
Junior Java Developer at Dotcode, a Ukrainian software company, building real products using Java, Spring Boot, Hibernate, and SQL databases (MySQL/PostgreSQL) with REST APIs, TDD/BDD, and agile practices in a small team.
Data Engineer - Senior 2
Senior data engineer at Cummins leading the design, development, and maintenance of a cloud-based data and analytics platform. Builds scalable data pipelines, data products, and AI/ML-ready datasets using Spark, Hadoop, SQL, Kafka, and modern ETL/ELT tools across Supply Chain, Finance, and Product domains.
Data Engineer - Senior 1
Senior Data Engineer at Cummins leading design and development of enterprise data pipelines and analytics platforms using Spark, Hadoop, Kafka, cloud data warehouses, and ETL/ELT tools, supporting analytics, AI/ML, and GenAI use cases across Supply Chain, Finance, and other domains.
Data Engineer 9
Data Engineer building and maintaining enterprise data pipelines, ETL/ELT transformations, and curated datasets across Supply Chain, Quality, Finance, and Product Lifecycle domains to power analytics, automation, and GenAI use cases using cloud big-data platforms.
Data Engineer 5
Data Engineer at Cummins building and maintaining enterprise-scale data pipelines, ETL/ELT transformations, and governed data products on cloud and Big Data platforms to support analytics, AI/ML, and GenAI use cases across Supply Chain, Quality, Finance, and Product Lifecycle domains.
Data Engineer 12
Data Engineer at Cummins building enterprise data products, pipelines, and curated datasets that support analytics, automation, and GenAI use cases across Supply Chain, Quality, Finance, and Product Lifecycle using Spark, Kafka, cloud platforms, SQL, and modern ETL/ELT tooling.
Data Engineer - Senior 6
Senior data engineer at Cummins designing and operating large-scale cloud data pipelines, data lakes, and ETL/ELT solutions using Spark, Scala/Java, Hive, HBase, Kafka, SQL, and NoSQL stores to deliver AI/ML- and analytics-ready data products across enterprise domains.
Data Engineer - Senior 4
Designs, builds, and optimizes reusable, governed enterprise data pipelines and cloud platforms for analytics, reporting, APIs, automation, and GenAI. The role spans SQL, Spark, Scala/Java, Kafka, Hadoop, ETL/ELT, data modeling, quality, lineage, and scalable data architecture.
Data Engineer 7
Cummins is hiring a Data Engineer in Pune to build and maintain enterprise data products—pipelines, transformations, and curated datasets—for Supply Chain, Quality, Finance, and GenAI use cases, using Spark, Scala/Java, Hadoop, Kafka, SQL, and cloud-based platforms in an Agile environment.