Data Engineer-Data Platforms-AWS

IBM; Maharashtra; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

IBM Consulting seeks a Data Engineer specializing in Data Platforms on AWS. You will design, build, and operate batch and real-time data pipelines, creating data layers on RedShift/Aurora/DynamoDB and migrating data with DMS. The role emphasizes open source tooling like Airflow and dbt, with Spark in Python/Scala on AWS.

You will work across projects, shaping hybrid cloud and AI journeys, while leveraging AWS services to enable scalable, reliable data solutions.

Qualifications

• Exposure to AWS Toolset and building batch and real-time data pipelines on the AWS Cloud.
• Experience developing data pipelines for Data Warehouse and Data Lake.
• Creation of data layers with RedShift, Aurora, and DynamoDB; data migration with DMS.
• Proficiency with open source tooling like Airflow and dbt; Spark in Python or Scala on AWS.

Responsibilities

• Design, build, and operate batch and real-time data pipelines on AWS.
• Create data layers on RedShift, Aurora, and DynamoDB; migrate data with DMS.
• Schedule and manage data services on the AWS Platform.
• Develop pipelines for Data Warehouse and Data Lake using Kinesis and MSK.
• Utilize open source tools like Airflow and dbt, Spark with Python/Scala on AWS.

Skills

AWS Services

Data Pipelines

Open Source Tools

Spark (Python)

Spark (Scala)

AWS DMS

Kinesis

dbt

Apache Airflow

Education

Master's Degree

Tools

AWS EMR

AWS Glue

Glue Catalog

Kinesis

RedShift

Aurora

DynamoDB

DMS

Apache Airflow

dbt

Spark (Python)

Spark (Scala)

Job description

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

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.

Your Primary Responsibilities Will Include

• Design and Develop Data Pipelines: Design, build, and operate batch and real-time data pipelines using AWS services such as AWS EMR, AWS Glue, Glue Catalog, and Kinesis, ensuring seamless integration and operation of data engineering solutions.
• Create Data Layers: Create data layers on AWS RedShift, Aurora, and DynamoDB, and migrate data using AWS DMS.
• Manage Data Services: Schedule and manage data services on the AWS Platform, ensuring efficient operation of data engineering solutions.
• Develop Batch and Real-time Pipelines: 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: Utilize open source technologies like Apache Airflow and dbt, Spark / Python or Spark / Scala on AWS Platform to support data engineering solutions.

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Exposure to AWS Toolset: Experience working with AWS services such as AWS EMR, AWS Glue, Glue Catalog, and Kinesis to design, build, and operate batch and real-time data pipelines.
• Data Pipeline Development: Exposure to developing batch and real-time data pipelines for Data Warehouse and Datalake, utilizing AWS Kinesis and Managed Streaming for Apache Kafka.
• Data Layer Creation: Experience working with AWS RedShift, Aurora, and DynamoDB to create data layers and migrate data using AWS DMS.
• Open Source Technologies: Exposure to utilizing open source technologies like Apache Airflow and dbt, Spark / Python or Spark / Scala on AWS Platform to support data engineering solutions.
• Data Service Management: Experience scheduling and managing data services on the AWS Platform, ensuring efficient operation of data engineering solutions.

Preferred Technical And Professional Experience

• Proficiency with AWS Databrew: Experience working with AWS Glue Databrew to support data engineering solutions, including data preparation and data quality tasks.
• Knowledge of Lambda Functions: Exposure to using Lambda functions with Python to support data engineering solutions, including data processing and data transformation tasks.
• Familiarity with RedShift Spectrum: Experience working with RedShift Spectrum to support data engineering solutions, including data warehousing and data analytics tasks.