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Big Data Developer Jobs (On-site work)

247 Job Offers

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Associate Data Scientist
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United States , Cleveland
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74484.80 - 116480.00 USD / Year
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University Hospitals
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Engineer, Data & Analytics
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United States , Philadelphia
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Comcast Advertising
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Senior Data Engineer
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India , Hyderabad
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Amgen
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Graduate Data Engineer
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United Kingdom , Skelmersdale
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Dover Precision Components
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Senior Microservices Backend Engineer
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India , Hyderabad
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Amgen
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Data Analytics Engineer II
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United States , Irving
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CHRISTUS Health
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Technical Project Manager
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United States , San Jose
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Thirdeye Data
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Data Engineer
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United Arab Emirates , Abu Dhabi
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Andersen
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Data Engineer
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Spain , Barcelona
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Yokoy
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Sensors Summer Internship
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United States , Woburn
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52000.00 - 79000.00 USD / Year
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STR
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Software Engineer - Platform
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United States , New York
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163200.00 - 223200.00 USD / Year
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Plaid
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Software Engineer - Platform
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United States , San Francisco
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163200.00 - 223200.00 USD / Year
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Plaid
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HPC Service Delivery Consultant
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Italy
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Hewlett Packard Enterprise
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Data Scientist
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India , Pune
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Citi
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Python Data Engineer
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India , Pune
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Citi
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AI/ML Engineer
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India , Chennai
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Citi
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Insights & Analytics Area Manager Growth & Marketing
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Sweden , Malmö
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IKEA
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Climate Risk Modeling VP
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India , Pune
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Citi
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Lead Full Stack Developer
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India , Pune
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Citi
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Manager, Data Science - Fiber Acquisition
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United States , Bellevue; Denver; Overland Park; Frisco
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133800.00 - 241400.00 USD / Year
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T-Mobile
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Discover a world of opportunity in Big Data Developer jobs, a critical and rapidly evolving career path at the heart of the modern data-driven economy. Big Data Developers are the master architects behind the systems that collect, process, and manage vast and complex datasets, transforming raw information into actionable business intelligence. These professionals are in high demand across virtually every industry, from finance and healthcare to e-commerce and technology, making this one of the most versatile and sought-after tech roles today. A Big Data Developer's primary mission is to design, build, test, and maintain robust and scalable data processing systems. Their day-to-day responsibilities are multifaceted and crucial to organizational success. Typically, they are tasked with designing and implementing end-to-end data pipelines that efficiently ingest data from diverse sources such as applications, databases, and IoT devices. They develop and optimize complex data processing workflows to ensure timely and accurate data availability for analytics and reporting. A significant part of their role involves performance tuning and monitoring of these large-scale systems to guarantee reliability and efficiency. Furthermore, they collaborate closely with data scientists, business analysts, and other stakeholders to understand data requirements and deliver solutions that empower data-driven decision-making across the company. To excel in Big Data Developer jobs, a specific and powerful skill set is required. Proficiency in programming languages is fundamental, with Python, Java, and Scala being the most common. A deep, practical understanding of the big data ecosystem is non-negotiable; expertise in frameworks and tools like Apache Hadoop, Apache Spark, Kafka, and Hive is standard. Knowledge of both SQL and NoSQL databases is essential for data storage and retrieval. As cloud platforms dominate the landscape, experience with services like AWS EMR, Azure HDInsight, or Google Cloud Dataproc is increasingly a core requirement. Beyond technical prowess, successful developers possess strong analytical and problem-solving skills to tackle complex data challenges, along with effective communication abilities to translate technical concepts for non-technical audiences. A bachelor's degree in computer science or a related field is typically expected, supplemented by several years of hands-on experience in data engineering or application development. For those with a passion for solving complex problems and building the infrastructure that powers modern analytics, Big Data Developer jobs offer a challenging, rewarding, and future-proof career. Explore these roles to become an integral part of turning massive data into monumental insights.

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