Data Engineer-Data Platforms-AWS
IBM
Bengaluru, Karnataka, India2h agovia LinkedIn
Posted 13 Nov 2026, 21:17 IST
This job at a glance
- Who can apply
- Freshers · Master's degree
- Must know
- ETLEHR / EMRScalaSparkAirflow
- Nice to have
- AWSPythonData analysis
- Work
- On-site in Bengaluru
- Pay
- Not stated by the employer.
- Listed
- 13 Nov 2026 · still open
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Data Engineer - Data Platforms - AWS
Company: IBM
About the Role
As a Data Engineer specializing in Data Platforms on AWS, you will advise on, develop, and maintain data engineering solutions on the AWS Cloud ecosystem. You will design, build, and operate batch and real-time data pipelines using various AWS services.
Key Responsibilities
- Design, build, and operate batch and real-time data pipelines using AWS services such as AWS EMR, AWS Glue, Glue Catalog, and Kinesis.
- Create data layers on AWS RedShift, Aurora, and DynamoDB, and migrate data using AWS DMS.
- Schedule and manage data services on the AWS Platform.
- Develop batch and real-time data pipelines for Data Warehouse and Datalake, utilizing AWS Kinesis and Managed Streaming for Apache Kafka.
- Utilize open-source technologies like Apache Airflow and dbt, Spark / Python or Spark / Scala on AWS Platform.
Requirements & Tech Stack
- Exposure to AWS services: AWS EMR, AWS Glue, Glue Catalog, Kinesis.
- Experience developing batch and real-time data pipelines for Data Warehouse and Datalake, utilizing AWS Kinesis and Managed Streaming for Apache Kafka.
- Experience with AWS RedShift, Aurora, and DynamoDB to create data layers and migrate data using AWS DMS.
- Exposure to open-source technologies: Apache Airflow, dbt, Spark / Python, Spark / Scala on AWS Platform.
- Experience scheduling and managing data services on the AWS Platform.
Qualifications
Preferred Education: Master's Degree
- Proficiency with AWS Glue Databrew for data preparation and data quality tasks.
- Exposure to using Lambda functions with Python for data processing and transformation.
- Experience with RedShift Spectrum for data warehousing and data analytics.