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IBM

Data Engineer-Data Platforms

IBM

Published 13 May 2026
India
Full Time

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Role Highlights

Languages used

Python

Key skills

Data Engineer
Data Analysis
Big Data
NLP
Machine Learning
Data Processing
Data Warehousing
Cloud
AI
API
Statistics
Modelling

Tools, Libraries and Frameworks

IOS
Red Hat
IBM

Description

The role involves developing applications on big data technologies and managing API development. Professionals will write and debug complex code to ensure the delivery of high-quality technical solutions. The position requires the application of technical expertise to build and maintain robust data platforms. Individuals will integrate various analytics and computing libraries to support data-driven objectives. The work focuses on creating innovative solutions that facilitate client impact and support hybrid cloud and AI initiatives.

Required Qualifications and Skills

The role requires a strong foundation in traditional application development and software development principles. Candidates must possess experience with big data technologies, API development, and data processing frameworks. Proficiency in integrating analytics libraries and utilizing open-source natural language processing tools is necessary. Additionally, the position requires knowledge of statistical and big data computing libraries. No specific degree or professional certification requirements are mentioned in the text.

Disclaimer

Disclaimer: Job and company description information and some of the data fields may have been generated via GPT-4 summarisation and could contain inaccuracies. The full external job listing link should always be relied on for authoritative information.

About the company

IBM

Size

305978

Website

ibm.com

HQ

Armonk, New York, US

Public/Private

Public Company

Description

IBM infuses core business operations with intelligence, from machine learning to generative AI, to make organizations more responsive, productive, and resilient. It helps clients put AI into action now, creating real value with trust, speed, and confidence across various areas like digital labor, IT automation, and security. The ability to utilize all data is critical, as AI's effectiveness is dependent on the quality of data fueling it, with IBM's AI, and data platform aiming to scale and accelerate AI's impact with trusted data. IBM's hybrid cloud platform offers a comprehensive approach to development, security, and operations across hybrid environments, laying a flexible foundation for leveraging data wherever it resides.

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