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IBM

Data Engineer-Data Platforms-AWS

IBM

Published 14 May 2026
Bangalore, India
Full Time

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Role Highlights

Languages used

Python
SCALA

Key skills

Data Engineer
Integrations
Open Source
Data Processing
Data Quality
Data Warehousing
Cloud
AI
Batch
Streaming
Transformation

Tools, Libraries and Frameworks

IOS
Red Hat
IBM
EMR
Kinesis
RedShift
Aurora
DynamoDB
Apache
Kafka
Airflow
Lambda

Description

The role involves advising on, developing, and maintaining data engineering solutions within the AWS Cloud ecosystem. Responsibilities include designing, building, and operating both batch and real-time data pipelines. The individual will create data layers and manage data services to ensure efficient operations. Additionally, the position requires the utilization of various open-source technologies to support data engineering tasks. The work focuses on supporting data warehouse and datalake environments to drive client impact.

Required Qualifications and Skills

The role requires technical expertise in the AWS toolset, specifically regarding the design and operation of batch and real-time data pipelines. Candidates must demonstrate experience in creating data layers and managing data services on the AWS platform. Proficiency in utilizing open-source technologies such as Apache Airflow, dbt, Spark, and Python or Scala is necessary. No specific degree or professional qualification 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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