Insight Global is seeking skilled AWS Data Engineers to join our banking client to support a large scale SaaS to AWS transformation project. Candidates will be involved in an initiative to build a new cloud platform tool in AWS for Wealth Data Solutions and moving data from Hadoop to AWS. The ideal candidates will have a strong background in data engineering, AWS webservices, and a strong understanding of data warehousing and batch processing. These individuals should be confident to work in an agile environment (Scrum, Kanban) and to collaborate with other functional roles in delivery including testing, analysis, architecture, and business stakeholders. Main themes for these individuals to consider are data storage, data movement, meta data & governance, infrastructure, and security/IAM. This role will hybrid in Toronto, ON on a 6 month contract with potential for extensions and conversion to full time.

Responsibilities:

- Perform data/file transformation using AWS services.

- Utilize AWS Glue for batch processing (Spark or Python).

- Implement data warehousing solutions using Amazon S3, Redshift (analytics and BI), Aurora/RDS (operational data stores).

- Ensure metadata and governance using AWS Glue Catalog, Lake Formation, and Macie.

- Create operational dashboards using AWS QuickSight and Power BI.

- Deploy and manage ML models in AWS SageMaker.

Required Skills & Experience:

- 8-10+ years of experience in data engineering, ideally in large enterprise banking/financial services environments.

- 8+ years of experience with AWS Services for data ingestion and movement including AWS Glue (batch processing and ETL), AWS Data Sync, AWS Transfer Family (SFTP).

- Excellent experience with data storage in AWS including AWS S3, Redshift (analytics and BI), Aurora/RDS (operational data stores).

- Experience with efficient data processing, querying, and serverless computing using AWS Athena, Redshift Spectrum, Lambda.

- Knowledge of metadata and governance using AWS Glue Catalog, Lake Formation (concepts/frameworks), and Macie (data recovery/protection)

- Expertise with data analytics and visualizations using AWS Quicksight and Power BI.

- Excellent communication skills with an ability to present ideas clearly to stakeholders.

Plusses:

- Expertise with ML models and frameworks in AWS SageMaker and AWS Redshift ML is highly preferred to incorporate ML models in data solution.

Hourly rate for this role starting at $65 depending on relevant skills & experience.