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IBM

Data Engineer-Data Platforms-Databricks

IBM

Published 10 May 2026
Hyderabad, India
Full Time

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Role Highlights

Languages used

Key skills

Data Engineer
Deep Learning
NLP
Data Governance
Machine Learning
Data Science
Data Processing
Data Warehousing
Cloud
AI
Architecture
Storage
Infrastructure
Deployment
Optimization
ETL

Tools, Libraries and Frameworks

IOS
Red Hat
IBM
DataBricks

Description

The role involves designing, developing, and deploying data and AI solutions on the Databricks platform to meet client requirements. The individual will collaborate with stakeholders to identify platform improvements and ensure optimal performance and scalability. Responsibilities include leading the delivery of data and AI solutions while working closely with clients to understand their needs. The position focuses on building and enhancing data platforms to drive business value through data-driven insights.

Required Qualifications and Skills

The role requires deep expertise in designing, developing, and deploying solutions on the Databricks platform. Candidates must possess strong data engineering skills, including experience with data processing, storage, and retrieval. Proficiency in cloud computing technologies and infrastructure management is necessary. Additionally, the position requires a proven track record in leading solution delivery and holding relevant certifications in data engineering, data science, or AI.

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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