- JOB IDENTIFICATION
Position Title : Data Engineer (Data Conversion - SQL and AWS)Department : CGI
- REPORTING RELATIONSHIPS
- Reports To: Kano Cannick
- Supervises: N/A
- Interfaces With: N/A
- DETAILS OF DUTIES AND RESPONSIBILITIES
- Key Responsibilities:
- Data Profiling & Analysis:
- Profile source system data to identify data quality gaps, mapping requirements, and transformation logic.
- Investigate data anomalies, trace root causes across related tables, and document findings for stakeholder review.
- Staging Pipeline Development:
- Design and maintain SQL staging views that transform legacy data into target system format.
- Create and maintain lookup/reference views that map source system codes to target platform values.
- Build stored procedures for data population and scope management across multiple product lines.
- Data Validation & Quality:
- Build and execute validation queries, reconciliation checks, and load report resolution workflows.
- Participate in iterative data quality cycles (profile, fix, reload, validate) until target thresholds are met.
- Implement data validation checks, monitor data quality, and address issues related to data integrity and accuracy.
- Collaboration with Stakeholders:
- Resolve load report findings and deliver clean data packages.
- Maintain ongoing communication with internal teams to ensure requirements are fully understood and reflected in delivered solutions.
- Provide regular updates on project progress, issues, and milestones.
- Automation & Tooling:
- Maintain and populate target staging databases in cloud environments (AWS RDS).
- Documentation & Knowledge Sharing:
- Document data mappings, transformation logic, product specifications, and data dictionaries.
- Create and maintain comprehensive technical documentation including SQL scripts, process workflows, and integration specifications.
- Share knowledge and expertise with team members, promoting best practices and fostering a culture of collaborative learning.
- Leverage AI coding assistants (e.g., Claude, Copilot) to accelerate SQL development, data profiling, script generation, and documentation.
- Write effective prompts to guide AI tools for complex data analysis, code generation, and automated reporting.
- Review, validate, and refine AI-generated outputs to ensure accuracy and alignment with business requirements.
- Continuous Learning & Innovation:
- Stay up to date with emerging data engineering technologies, AI tooling, and best practices to improve solution delivery.
- Absorb insurance domain knowledge through mentorship, documentation review, and hands-on data exploration.
- Code Quality and Best Practices:
- Write clean, efficient, and maintainable code, adhering to coding standards and best practices.
- QUALIFICATION STANDARDS
- Work Experience:
- 2-5 years of experience
- Proficiency in SQL Server (queries, views, stored procedures, CTEs, window functions) and ETL (Extract, Transform, Load) processes
- AWS: RDS, S3, Secrets Manager, or equivalent cloud database experience
- Proficiency in Excel for data analysis and legacy data review
- GitHub
- Experience with project management software (e.g., Jira)
- Expertise in Agile methodologies (e.g., Kanban, Scrum) for managing delivery
- Experience ensuring secure data handling, especially sensitive financial data and personally identifiable information (PII)
- Proficient in data validation and data cleansing practices
- Experience using AI coding assistants (Claude, GitHub Copilot, or similar) for development workflows, prompt engineering, and automated analysis
- Competencies and Skills:
- Excellent communication and interpersonal skills, capable of conveying complex technical concepts to non-technical stakeholders.
- Strong problem-solving abilities and analytical thinking.
- Self-directed learner who thrives with mentorship - eager to absorb insurance domain knowledge and conversion methodology.
- Ability to work on multiple projects simultaneously while ensuring high-quality delivery.
- Attention to detail, with a focus on delivering accurate and validated data.
- Highly Preferred:
- Prior data migration/conversion project experience
- Experience with policy administration systems
- Experience in the insurance/financial industry
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