Business Lines

Nexon Staffings is renowned for its forward-thinking approach, always striving to stay one step ahead in today's fast-paced technology marketplace. With our deep expertise and foresight, we have the ability to connect you with the most skilled and experienced talent, essential for excelling in the dynamic Big Data arena. Our team comprises seasoned professionals who excel at delivering top-notch solutions on time and within budget. Whether you require onsite, remote site, or software development projects, or need staff augmentation services, we have the capabilities to cater to your specific needs and ensure successful outcomes.

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In today's data landscape, one thing is certain - data will continue to grow at an unprecedented rate. Terabytes are now considered old news; the talk is all about petabytes, zettabytes, and beyond. Are you prepared to handle the challenges of Big Data? Do you know what steps you need to take with Big Data? Do you have the necessary resources with expertise in Big Data?

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Nexon Staffings is a forward-thinking company that takes pride in staying ahead of the curve in today's rapidly evolving technology market. Leveraging our expertise, we can connect you with the most qualified and experienced talent to help you navigate the world of Big Data. Our team members have the experience and skills to deliver top-quality results, meeting deadlines and budget constraints. We offer a range of services, including onsite and remote support, software development projects, and staff augmentation services. Whatever your Big Data needs are, we've got you covered.

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 Our positions including but not limited to:

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• Data Scientist: Analyzes and interprets complex data sets to identify patterns, trends, and insights that can drive business decisions.

• Big Data Engineer: Designs and develops large-scale data processing systems and architectures to handle and store massive volumes of data.

• Data Analyst: Collects, cleans, and analyzes data to provide actionable insights and support decision-making processes.

• Data Architect: Designs and oversees the structure and organization of data systems to ensure efficient storage, retrieval, and processing of data.

• Data Warehouse Manager: Manages the storage, retrieval, and security of large-scale data in data warehouses.

• Hadoop Developer: Specializes in programming and developing applications on the Hadoop ecosystem to process and manage Big Data.

• Machine Learning Engineer: Develops and deploys machine learning models to extract valuable information and predictions from large datasets.

• Data Mining Specialist: Utilizes data mining techniques to discover patterns and relationships in vast data sets.

• Business Intelligence (BI) Analyst: Transforms raw data into actionable insights and reports to support business decision-making.

• Data Quality Analyst: Ensures the accuracy and integrity of data by implementing data quality processes and conducting quality checks.

• NoSQL Database Administrator: Manages and optimizes NoSQL databases used for handling Big Data.

• Data Governance Manager: Develops and enforces policies and procedures for data management, security, and privacy.

• Data Integration Specialist: Integrates and combines data from multiple sources to create unified and cohesive datasets.

• Spark Developer: Specializes in developing applications on the Apache Spark framework for Big Data processing.

• Data Visualization Specialist: Creates visual representations of data to aid in understanding and communication of insights.

• Chief Data Officer (CDO): Leads data-related initiatives and strategies at the executive level to ensure data-driven decision-making throughout the organization.

• Data Privacy Officer: Ensures compliance with data protection regulations and manages data privacy policies and procedures.

• Data Operations Manager: Oversees the day-to-day operations of data systems, ensuring smooth data processing and storage.

• Data Science Manager: Leads and supervises data science teams, guiding them in conducting data analysis and modeling.

• Real-time Data Analyst: Analyzes streaming data in real-time to provide immediate insights and responses.

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