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BULL INFORMATION SYSTEMS LIMITED · Toronto, Ontario, Canada

ETL Data Engineer - AWS & Netezza

entry_levelfull timePosted 2 days ago
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Stack mentioned

etlawss3serverlessredshiftci/cddata-engineeringdata-warehousingidentity-and-access-managementapache-sparkdata-governanceunit-testing

Required Skills:

Extensive experience in Data Warehousing, Data Engineering, and AWS Cloud technologies.

Strong domain knowledge in Banking and Financial Services.

Experience designing and implementing large-scale data platforms and migration initiatives.

Technical Skills (Must Have)

Amazon S3 (Data Lake)

AWS Glue (ETL)

AWS Lambda

Amazon Redshift

AWS Step Functions

AWS IAM

AWS CloudWatch

IBM Netezza

ETL/ELT Design and Development

Data Warehouse Architecture

Data Migration and Modernization

CI/CD Pipeline Implementation

Key Responsibilities:

Data Engineering & Development

Design, develop, and maintain scalable data pipelines and workflows on AWS.

Build and manage enterprise data lakes and data warehouses using AWS services such as Amazon S3 and Amazon Redshift.

Develop and maintain ETL/ELT processes using AWS Glue, AWS Lambda, Apache Spark, and related technologies.

Implement robust data ingestion frameworks including batch processing and streaming solutions.

Optimize data ingestion, transformation, and data loading processes for performance and scalability.

Monitor, troubleshoot, and support data pipelines and workflows.

Cloud & Architecture:

Design cloud-native data solutions leveraging AWS services and best practices.

Ensure data quality, governance, security, and compliance standards are met.

Implement and manage monitoring solutions using AWS CloudWatch.

Manage access controls and security configurations using AWS IAM.

Improve platform performance, scalability, reliability, and cost optimization.

Migration & Modernization:

Analyze and understand existing IBM Netezza implementations.

Design and implement migration strategies from Netezza to AWS Data Lake architecture.

Ensure feature parity and optimal performance in the target AWS environment.

Support deployment and migration activities through to production.

Testing & Deployment:

Perform unit testing and support QA, SIT, performance, and user acceptance testing activities.

Automate deployment processes using CI/CD pipelines.

Support production releases and post-deployment validation activities.

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