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Data Engineering Challenge Participation | Nedbank N*ovation Data and Analytics Masters 2026

Issued by Otinga.io

This badge recognises participation in the Data Engineering track of the Nedbank N*ovation Data and Analytics Masters 2026. Working individually on their own schedule, the recipient took on a production-grade banking data challenge: building a medallion pipeline that ingests realistic fintech and bank data through Bronze, Silver and Gold layers into a clean, auditable dimensional model in Delta Parquet. They packaged their solution as a reproducible, Docker-based Git repository and submitted it on the Otinga platform. It's not a quiz or a timed exercise - it's real engineering, judged the way production code is judged. Taking it on is something to be proud of, and a real step in growing as a data engineer.

Recipient: James Myburg
Issued On: June 24, 2026, 1:41 p.m.
Certificate ID: 06224f40-8d1c-4f48-8d55-cfe32d477d9b

Earning Criteria

  • Active Participation in the Challenge
    • Registered for and took part in the Data Engineering track of the Nedbank N*ovation Data and Analytics Masters 2026.
    • Worked individually on a production-grade engineering problem during the competition window, on their own schedule.
  • Building a Medallion Data Pipeline
    • Designed a pipeline to process three data sources through Bronze, Silver and Gold layers into a dimensional model in Delta Parquet.
    • Tackled real-world data realities - multiple formats, deduplication, schema enforcement and account-to-customer linkage.
  • Application of Data Engineering Skills
    • Contributed working code using tools of their choice within the provided Docker environment (for example PySpark, DuckDB, pandas, Polars or dbt).
    • Engineered for correctness, scalability, maintainability, efficiency and reproducibility.
  • Engagement with the Challenge Process
    • Built and tested locally against the provided testing harness and interface contract.
    • Submitted a Git repository URL on the Otinga platform before the deadline.
  • Completion of Core Deliverables
    • Produced the required repository structure, including a Dockerfile and the ingest, transform and provision entry points.
    • Delivered a pipeline intended to run end-to-end within the enforced resource and time limits.
  • Commitment to Learning & Professional Growth
    • Took on a challenging, realistic banking scenario and built for production reality rather than a quick fix.
    • Met the AI-usage disclosure and explainability expectations, owning and understanding every part of the submission.