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IBM

Data Engineer-Data Platforms

IBM

Published 09 Apr 2026
Bangalore, India
Full Time

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Role Highlights

Languages used

Key skills

Machine Learning
Data Engineer
Big Data
NLP
Data Processing
Data Visualization
Cloud
AI
API
Statistics
Modelling
Storage
NOSQL
Database

Tools, Libraries and Frameworks

IOS
Red Hat
IBM

Description

The role involves developing applications on Big Data technologies and managing API development. The individual will write and debug complex code to ensure the delivery of high-quality technical solutions. Responsibilities include applying knowledge of open-source Natural Language Processing and statistical computing libraries to build robust data platforms. The position focuses on implementing Big Data technologies to support the creation of data-driven solutions. The individual will collaborate with clients to help shape their hybrid cloud and AI journeys.

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, including 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 an understanding of statistical and big data computing libraries to address real-world problems. No specific degree or professional certification is mentioned in the posting.

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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