Job Title: AWS Cloud Data Engineer
Location: Toronto, ON
Work Model: Onsite
Employment Type: Full-Time (FTE)
Experience: 10+ Years
Job Overview
We are seeking an experienced AWS Cloud Data Engineer with strong expertise in data engineering, data warehousing, and AWS cloud technologies. The ideal candidate will have hands-on experience building scalable data platforms, developing ETL/ELT pipelines, and supporting large-scale data migration and modernization initiatives, particularly within the Banking and Financial Services domain.
The role will focus heavily on modernizing legacy IBM Netezza workloads and migrating data platforms to AWS-based data lake and data warehouse architectures.
Required Technical Skills
- Strong experience in Data Engineering, Data Warehousing, and AWS Cloud
- Amazon S3 – Data Lake architecture and implementation
- AWS Glue – ETL/ELT development
- AWS Lambda – Serverless data processing
- Amazon Redshift – Data warehousing
- AWS Step Functions – Workflow orchestration
- AWS IAM – Identity, access management, and security
- AWS CloudWatch – Monitoring and operational support
- IBM Netezza – Development, administration, or migration experience
- ETL/ELT design and development
- Data warehouse architecture and data modeling
- Data migration and modernization
- CI/CD pipeline implementation
- Apache Spark and distributed data processing
- Strong understanding of data security, governance, quality, and compliance
Key Responsibilities
Data Engineering & Development
- Design, develop, and maintain scalable AWS-based data pipelines and data processing workflows.
- Build and manage enterprise data lakes and data warehouses using Amazon S3, Amazon Redshift, and related AWS services.
- Develop robust ETL/ELT pipelines using AWS Glue, Lambda, Apache Spark, and other data engineering technologies.
- Implement batch and streaming data ingestion frameworks.
- Develop reusable frameworks for data ingestion, transformation, validation, and loading.
- Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
- Monitor, troubleshoot, and resolve data pipeline and workflow issues.
- Implement data quality checks and validation processes across data pipelines.
AWS Cloud & Data Architecture
- Design and implement cloud-native data solutions following AWS architecture and engineering best practices.
- Develop scalable and highly available data architectures for enterprise workloads.
- Implement security and access controls using AWS IAM and other AWS security capabilities.
- Configure and maintain operational monitoring and alerting using AWS CloudWatch.
- Ensure data platforms meet organizational requirements for security, governance, privacy, quality, and compliance.
- Identify opportunities to improve platform performance, scalability, reliability, and cloud cost optimization.
Data Migration & Modernization
- Analyze existing IBM Netezza environments, workloads, data structures, and ETL processes.
- Design and implement migration strategies from IBM Netezza to AWS-based data lake and data warehouse platforms.
- Develop migration pipelines and transformation processes to move legacy workloads to AWS.
- Validate data completeness, accuracy, performance, and functionality following migration.
- Ensure appropriate feature parity and optimize workloads for the target AWS environment.
- Support migration activities across development, testing, deployment, and production environments.
- Troubleshoot migration-related data and performance issues.
Testing & Deployment
- Develop and execute unit tests for data pipelines and transformation logic.
- Support QA, SIT, UAT, regression, and performance testing activities.
- Implement automated deployment processes using CI/CD pipelines.
- Promote data engineering solutions across development, QA, and production environments.
- Support production releases, deployment validation, and post-production stabilization.
- Maintain technical documentation for data pipelines, architectures, migration processes, and operational procedures.
Domain Experience
- Strong experience in Banking and Financial Services environments.
- Understanding of enterprise banking data, financial data platforms, regulatory requirements, and data governance.
- Experience working with large-scale enterprise data migration or modernization programs is highly preferred.
Preferred Qualifications
- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field.
- Strong problem-solving and analytical skills.
- Experience working in Agile/Scrum development environments.
- Excellent communication and collaboration skills.
- Ability to work effectively with data architects, developers, QA teams, business stakeholders, and cloud engineering teams.
