Scoring Format:
1. Roles & Responsibilities: 8/10
2. Years of Experience: 6/10
3. Education Qualification: 0/10
4. Skills/Knowledge: 6/10
5. Domain/Industry: 0/10
6. Key Competencies: 0/10

Descriptive Analysis:
Overall Summary:
- The candidate's resume shows relevant experience in data modeling and data engineering, with a focus on data warehouse projects in the telecom, insurance, and supply chain domains.
- The candidate has experience in requirement gathering, data modeling using Erwin, and working with data warehouse environments.
- They have experience in managing business requirements as a Scrum master and have good knowledge of the software development life cycle (SDLC) and software testing life cycle (STLC).
- The candidate has experience with ETL testing, database testing, and automation.
- They have worked with various databases such as Teradata, Oracle, and SQL Server, and have knowledge of data modeling tools like Erwin.
- The candidate has experience with ETL tools like Abinitio, Datastage, Informatica, and Azure Data Factory (ADF).
- They have experience with SQL, C, VB Script, and Excel Macro (VBA).
- The candidate has experience in working with clients, prioritizing responsibilities, and has good communication skills.
- They have experience in working in an Agile environment and have a data-driven mindset.
- The resume does not provide information about the candidate's education qualification, domain/industry knowledge, or key competencies.

Based on the above analysis, the candidate aligns well with the roles and responsibilities mentioned in the job requirements, scoring 8/10. They have relevant experience in data modeling and data engineering, and have worked on data warehouse projects in the telecom domain. They have experience with data modeling tools like Erwin and have implemented data quality rules. However, the candidate falls short in terms of years of experience, scoring 6/10, as they have 4-5 years of hands-on PL/SQL development experience instead of the required 6+ years of industry experience. The resume does not provide information about the candidate's education qualification, domain/industry knowledge, or key competencies, scoring 0/10 for each. Overall, the candidate shows relative strengths in data modeling and data engineering, but lacks in some of the specific job requirements.