Data Engineering Internship 2026
Chapter 11
Capstone Evaluation Rubric
Your capstone is evaluated across four technical areas (25% each) and a set of professional criteria. Each technical criterion uses a 1–4 scale.
Quick Reference
Novice (1): Basic understanding, limited application
Developing (2): Can apply with guidance and examples
Proficient (3): Applies correctly and independently — this is the target level
Advanced (4): Optimises, extends, and demonstrates depth beyond requirements
SQL — 25%
| Criterion | Weight | To reach Proficient (3) |
|---|---|---|
| Database schema design | 5% | Designs normalized tables with proper constraints and indexes |
| Table relationships | 5% | Implements 1:N and N:M relationships correctly |
| Advanced SQL (LAG, LEAD, window functions) | 10% | Writes queries using window functions correctly for analytics |
| Query optimization | 5% | Optimises queries using indexes and EXPLAIN plans |
Python / Pandas — 25%
| Criterion | Weight | To reach Proficient (3) |
|---|---|---|
| Python classes | 5% | Uses classes for modular, reusable code |
| Data processing functions | 10% | Writes modular, reusable functions for data pipelines |
| Pandas operations | 10% | Uses advanced Pandas methods (pivot, melt, apply) correctly |
dbt — 25%
| Criterion | Weight | To reach Proficient (3) |
|---|---|---|
| SQL and modelling logic | 10% | Clear use of CTEs. Logic is modular and follows DRY principles |
| Project structure | 5% | Follows dbt best practices: staging, intermediate, and mart layers clearly separated |
| Testing and documentation | 5% | Includes generic tests (unique, not_null) and descriptions for all models |
| source() and ref() | 5% | Properly uses source() for raw data and ref() for downstream models |
Power BI — 25%
| Criterion | Weight | To reach Proficient (3) |
|---|---|---|
| Data model design | 5% | Designs star/snowflake schema correctly for reports |
| Calculations and measures | 10% | Implements intermediate DAX (time intelligence, variables) |
| Data storytelling | 10% | Designs dashboards with clear insights and visuals |
Professional Criteria
| Criterion | What it looks like at a good level |
|---|---|
| Communication | Asks clear questions. Updates the team proactively. Explains technical decisions plainly. |
| Time management | Meets activity deadlines. Raises blockers early, not at the last minute. |
| Professional tone | Respectful in all communications. Takes feedback constructively. |
| Proactiveness | Does not wait to be told what to do. Takes initiative on blockers and improvements. |
| Curiosity | Reads beyond the required materials. Explores alternative approaches. |
| Learning drive | Tracks own gaps. Does not repeat the same mistakes. Seeks understanding, not just answers. |
| Presentation skills | Organises ideas clearly. Stays within time. Handles questions confidently. |