Data Engineer-Data Platforms-AWS

IBM; Maharashtra; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

IBM Consulting seeks a Data Engineer specializing in Data Platforms on AWS to advise on, develop, and maintain data engineering solutions across the AWS Cloud ecosystem. You will design, build, and operate batch and real-time data pipelines using services such as EMR, Glue, Kinesis, and DMS to support data warehouses and data lakes.

The role requires expertise with Airflow, dbt, Spark in Python/Scala, and experience with RedShift Spectrum; a Master's degree is preferred to contribute to IBM's AI

Qualifications

• Experience with AWS toolset (EMR, Glue, Glue Catalog, Kinesis) for batch and real-time data pipelines.
• Development of data pipelines for Data Warehouse and Data Lake using Kinesis and Kafka.
• Creation of data layers on RedShift, Aurora, DynamoDB and data migration with DMS.
• Proficiency with open source data tooling (Airflow, dbt) and Spark with Python/Scala on AWS.
• Experience scheduling and managing data services on AWS.

Responsibilities

• Design and develop data pipelines (batch and real-time) on AWS services.
• Create data layers on RedShift, Aurora, DynamoDB; migrate data with DMS.
• Manage data services on the AWS Platform to ensure efficient operation.
• Develop pipelines for Data Warehouse and Data Lake using Kinesis and Kafka.
• Use Open Source technologies like Airflow and dbt with Spark/Python or Spark/Scala.

Skills

AWS EMR

AWS Glue

Kinesis

RedShift

Aurora

DynamoDB

DMS

Airflow

dbt

Spark

Python

Scala

Lambda

RedShift Spectrum

Databrew

Education

Master's Degree

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.

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.