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IBM

Data Engineer-Data Platforms-Azure

IBM

Published 08 May 2026
Bangalore, India
Full Time

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Role Highlights

Languages used

SQL
Python
SCALA

Key skills

Data Engineer
Open Source
Cloud
AI
Batch
Database
Storage
Streaming

Tools, Libraries and Frameworks

Data Factory
Azure Databricks
IOS
Red Hat
IBM
DataBricks
Apache
Airflow
Kafka

Description

The individual in this role will advise on, develop, and maintain data engineering solutions within the Azure Cloud ecosystem. Responsibilities include designing, building, and operating both batch and real-time data pipelines. The role involves developing the data layer using various cloud-based storage and analytics services. Additionally, the professional will implement open-source technologies to support data engineering solutions. The position requires operating a variety of streaming and data processing services to ensure effective data management.

Required Qualifications and Skills

The role requires professional experience with the Azure toolset, specifically in designing and operating batch and real-time data pipelines. Candidates must demonstrate proficiency in Azure Data Platform components and the ability to implement open-source technologies such as Apache Airflow, dbt, Spark, Python, or Scala. Experience operating services like Azure Event Hub, Streaming Analytics, and Managed Streaming for Apache Kafka is necessary. No specific degree or professional certifications are explicitly mentioned as requirements for this position.

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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