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Java Big Data Engineer Jobs

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Software Engineer
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United Kingdom , Edinburgh
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Addepar
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Principal Applied Scientist
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United States , Mountain View
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139900.00 - 274800.00 USD / Year
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Microsoft Corporation
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AI Engineer
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Portugal , Lisbon
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We Are Meta
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Machine Learning Engineer
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Poland
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RTB House
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Senior Lead Data Engineer
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United States , McLean; New York; Richmond
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209000.00 - 286200.00 USD / Year
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Capital One
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Director, Software Engineering
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United States , Pleasanton, California
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251000.00 - 314500.00 USD / Year
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BlackLine
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Senior Software Engineer, Machine Learning
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United States , Austin
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Roku
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Java Back End Developer
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United States , Kennesaw
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CPC Technologies
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Director, Software Engineering
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India , Bengaluru
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BlackLine
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Senior Software Engineer
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United States , Annapolis Junction
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2HB
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Java Back End Developer
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United States , Kennesaw
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CPC Technologies
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Senior Data Scientist
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Israel , Tel Aviv
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Taboola
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Federal Senior Solutions Architect
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181800.00 - 213700.00 USD / Year
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Confluent
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Core Java Software Developer
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TIGER
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Programmer Analyst
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United States , Edison
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SmallArc
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Data Architect/Databricks Consultant
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India , Hyderabad
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Genzeon
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Software Developer
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United States , East Brunswick
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eGrove Systems
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Senior Quality Analyst
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India , Pune
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Citi
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Architecture Lead Analyst
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Ireland , Dublin
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Citi
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Monitoring & Observability Engineer
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India , Chennai; Pune
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Citi
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Explore the dynamic world of Java Big Data Engineer jobs, a high-demand career at the intersection of robust software engineering and massive-scale data processing. A Java Big Data Engineer is a specialized professional who designs, builds, and maintains the large-scale data infrastructure and applications that allow organizations to harness the power of big data. This role is critical in today's data-driven economy, transforming vast and complex datasets into clean, structured, and actionable information for analytics, machine learning, and business intelligence. Professionals in this field typically engage in the full lifecycle of data-centric applications. Their common responsibilities include architecting and developing scalable data pipelines, which are the automated systems that collect, ingest, process, store, and distribute data. They write complex data processing logic to clean, aggregate, and transform data from diverse sources into usable formats. A significant part of their role involves optimizing these data systems for performance, reliability, and efficiency to handle terabytes or petabytes of information. They also ensure data quality, implement robust data security measures, and collaborate closely with data scientists, analysts, and other business stakeholders to understand data requirements and deliver effective solutions. The typical skill set for these jobs is a powerful blend of deep software engineering expertise and specialized big data technologies. Core Java proficiency is fundamental, often extended with knowledge of modern frameworks like Spring Boot and Microservices for building resilient applications. Mastery of the big data ecosystem is essential, including distributed computing frameworks like Apache Spark and Apache Hadoop (encompassing HDFS). Experience with real-time data streaming platforms such as Apache Kafka is also a common requirement. Furthermore, these engineers are expected to be proficient in both SQL and NoSQL databases, understand data warehousing concepts, and utilize workflow orchestration tools like Apache Airflow to automate and monitor data pipelines. Typical requirements for Java Big Data Engineer jobs often include a degree in computer science or a related field and several years of relevant professional experience. Success in this role also demands strong analytical and problem-solving skills to tackle complex data challenges. Experience working in an Agile development environment is highly valued, as is a solid understanding of distributed systems architecture and containerization technologies like Docker and Kubernetes. For those seeking a challenging and rewarding career path, Java Big Data Engineer jobs offer the opportunity to work on cutting-edge technology and play a pivotal role in shaping an organization's data strategy.

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