_{08th January, 2025}

This is an independent consultant position for contract work with a Kyndryl client and is not a direct staff position with Kyndryl
 
 
Position: ETL Data Consultant
Client: Public Sector
Location: Remote, National Capital Region Preferred
Duration: 9-month initial contract
Security Clearance: Enhanced reliability
Language: English
 
 
Background: 
 
Kyndryl Canada is supporting our public sector client in the design, development, and implementation of a secure and scalable data integration and management solution. This Data Layer project aims to streamline data processes and ensure seamless accessibility while maintaining the highest standards of security.
We are seeking a highly skilled ETL Data Consultant to play a pivotal role in creating a robust architecture to automate the ingestion, transformation, storage, and access of data. You will be working with AWS services such as Glue, S3, Athena, Lambda, and API Gateway to build scalable and efficient solutions.
 
Qualifications:
 

• Relevant AWS Certification (preferably in data-related AWS services such as AWS Glue, S3, Athena).
• Extensive hands-on experience with AWS Glue, Amazon S3, Amazon Athena, AWS Lambda, and API Gateway.
• Degree or Diploma in Technology, Engineering, or Project Management or related field.
• Active Government of Canada security clearance (mandatory)

 
 
Expected Tasks:
 
Design and Architecture:

• Analyze requirements for scalable metadata management.
• Map data sources with schemas and metadata.
• Create visual documentation of the architecture.
• Evaluate tools and technologies for implementation.

Data Integration:

• Develop ETL processes for metadata extraction and transformation.
• Configure direct connections to metadata management solutions.

Metadata Storage and Tagging:

• Set up databases or data warehouses for metadata.
• Design data models for efficient storage and retrieval.
• Implement security protocols for data access.

API Development:

• Gather API requirements and implement with cost consideration.
• Document API endpoints and input/output formats.
• Conduct API testing.

Data Governance:

• Develop policies for data quality and compliance.
• Set up automated data quality checks.
• Ensure adherence to regulations through regular reviews.

Collaboration:

• Meet with teams to gather feedback and requirements.
• Ensure integration with the Enterprise Data Catalogue.
• Record decisions and insights.

Documentation:

• Maintain solution documentation using Azure DevOps Wiki.
• Create end-user guides for ease of use.

Performance Monitoring:

• Monitor system performance and usage.
• Optimize the metadata management solution.

Troubleshooting:

• Investigate and resolve issues.
• Document solutions for future reference.

Data Training and Support:

• Create resources for data management best practices.
• Organize training sessions for the data team.

 
 
 

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