\\\\Introduction\\\\ A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. Youll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, youll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. Youll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. \\\\Your role and responsibilities\\\\ As a Data Engineer specializing in Data Platforms, you will develop applications on Big Data technologies, including API development. This role requires a strong foundation in traditional Application Development, along with knowledge of Analytics libraries, open-source Natural Language Processing, and statistical and big data computing libraries. Your primary responsibilities will include: Design and Develop Applications: Develop applications on Big Data technologies, including API development, utilizing expertise in traditional Application Development and knowledge of Analytics libraries. Write and Debug Code: Write and debug complex code, applying technical abilities to ensure high-quality solutions. Apply Technical Expertise: Apply knowledge of open-source Natural Language Processing, and statistical and big data computing libraries to deliver robust data platforms. Implement Big Data Technologies: Implement Big Data technologies to support the development of data-driven solutions. Deliver High-Quality Solutions: Deliver high-quality solutions, leveraging exceptional technical abilities to meet business needs. \\\\Required technical and professional expertise\\\\ Traditional Application Development: Exposure to developing applications using traditional methods, with a strong foundation in software development principles. Big Data Technologies: Experience working with Big Data technologies, including API development and data processing frameworks. Analytics Libraries: Exposure to Analytics libraries, with knowledge of how to integrate them into data-driven solutions. Open-Source Natural Language Processing: Experience working with open-source Natural Language Processing tools and techniques. Statistical and Big Data Computing: Exposure to statistical and big data computing libraries, with an understanding of how to apply them to real-world problems. \\\\Preferred technical and professional experience\\\\ Advanced Analytics Knowledge: Exposure to machine learning algorithms, predictive modeling, and data visualization techniques to further enhance data-driven solutions. Cloud-Based Big Data: Experience working with cloud-based Big Data technologies, including cloud storage and cloud computing platforms. NoSQL Database Expertise: Exposure to NoSQL databases, with knowledge of how to design and implement scalable data storage solutions. IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.

The role requires a strong foundation in traditional application development and software development principles. Experience working with Big Data technologies, including API development and data processing frameworks, is necessary. Knowledge of Analytics libraries and how to integrate them into data-driven solutions is expected. Experience with open-source Natural Language Processing tools and techniques is also required. Exposure to statistical and big data computing libraries and their application to real-world problems is needed.