Data Engineer-Data Platforms-AWS

IBM; Hyderabad; On-site; INR 1,800,000 - 2,800,000; Full time

Job summary

IBM in Hyderabad, India is seeking a Data Engineer specializing in Data Platforms on AWS to design, build, and operate batch and real-time data pipelines on the AWS Cloud ecosystem.

You will leverage AWS EMR, Glue, Kinesis, RedShift, Aurora, DynamoDB, DMS, Airflow, and dbt to create data layers and manage data services, enabling data warehouses and datalakes.

Strong collaboration with analytics teams and a focus on scalable, reliable data processing will be essential.

Qualifications

• Exposure to AWS toolset including AWS EMR, AWS Glue, Glue Catalog, and Kinesis.
• Experience designing batch and real-time data pipelines for Data Warehouse and Datalake.
• Experience creating data layers with RedShift, Aurora, and DynamoDB and migrating data using DMS.
• Exposure to utilizing open source technologies like Apache Airflow and dbt, Spark / Python or Spark / Scala on AWS Platform to support data engineering solutions.
• Experience scheduling and managing data services on the AWS Platform, ensuring efficient operation of data engineering solutions.
• Bachelor's Degree in a relevant field.

Responsibilities

• 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 on AWS RedShift, Aurora, and DynamoDB, and migrate data using AWS DMS.
• Manage data services on the AWS Platform, scheduling and ensuring efficient operation of data engineering solutions.
• Develop batch and real-time 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 to support data engineering solutions.

Skills

Batch & real-time pipelines

Data Lake & Warehouse

Open Source tools

Python programming

Spark

SQL

Education

Bachelor's Degree

Master's Degree

Tools

AWS EMR

AWS Glue

Glue Catalog

Kinesis

RedShift

Aurora

DynamoDB

DMS

Airflow

dbt

Spark

Python

Scala

Kafka

Job description

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 education

• Bachelor's Degree

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.

Years of Experience: 5 - 8