Data Engineer-Data Platforms-AWS

IBM Computing; Pune District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

IBM Consulting in Pune invites a Data Engineer specializing in AWS to design, build, and operate scalable data pipelines for data warehouse and data lake solutions on the AWS cloud. You will work with open source tools like Airflow and dbt, and leverage services such as EMR, Glue, RedShift, DynamoDB, and Kinesis to deliver real-time and batch data processing.

This role involves collaboration with analytics and engineering teams and growing within a global consulting environment.

Qualifications

• Experience designing data pipelines on AWS for batch and real-time processing.
• Hands-on with Data Warehouse and Data Lake architectures on AWS.
• Proficiency with Open Source data tooling (Airflow, dbt).

Responsibilities

• Design, build, and operate batch and real-time data pipelines on AWS.
• Create data layers using RedShift, Aurora, and DynamoDB and migrate data with DMS.
• Manage data services and scheduling on the AWS platform.
• Develop pipelines for Data Warehouse and Data Lake with Kinesis and Kafka.
• Utilize Airflow and dbt to support data engineering solutions.

Skills

AWS

Data pipelines

Python

Scala

Open source

Tools

AWS EMR

AWS Glue

Kinesis

Redshift

DynamoDB

Aurora

dbt

Airflow

Job description

Introduction

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.

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.

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.