Nguyen Vu

Final-year Computer Science student with production engineering experience in a large, regulated environment: Python, PySpark, SQL, Spark, testing, code review and CI/CD. Experienced in root-cause analysis of slow and failing jobs, data quality, lineage and governance, reviewing other engineers' work, and communicating findings to non-technical stakeholders.

Graduating

May 2027, available from June 2027.

Data Engineer Intern at Inland Revenue Authority of Singapore (IRAS) (2026-01 – 2026-08)

• Built and maintained data warehouse pipelines for 25+ production ETL tables on tables up to 25.2M rows, reimplementing undocumented legacy logic in PySpark and SQL; scripts deployed and scheduled for live production runs.
• Built a full-row subtract validation framework in Spark SQL, Hive and Impala with root-cause triage, driving a 16.2M-row table from 15,093 differing rows to zero and recovering ~92,000 missing records via two defect fixes.
• Extended a Python model-inference microservice: traced its Jinja-templated SQL generation and implemented persistence of rule-evaluation records to MongoDB, shipped as unit-tested pull requests under team code review.
• Reviewed another developer's PySpark conversion, identifying 5 defects including a fan-out join, a non-deterministic grouping and a wrong-grain aggregation; supported a script owner through her first production run, diagnosing a failure remotely.
• SQL performance optimization: benchmarked ODBC SQL pass-through on tables up to 92M rows, pushing filters and joins into the database and turning timed-out queries into sub-minute runs; documented for team-wide adoption.
• Automated recurring quality checks and rolled shared cleansing, extraction and timestamp utilities across every team notebook, removing whole categories of discrepancy.
• Resolved out-of-memory failures and a data-skew straggler via broadcast joins, native Spark expressions over Python UDFs, Parquet checkpointing, and tuning spark.sql.shuffle.partitions.
• Built an Azure ML data-drift detector, implementing Kolmogorov–Smirnov and Chi-squared tests directly in Python across 38 features when the planned library was firewall-blocked.

AI Intern at BKAV - Cybersecurity Corporation (2024-11 – 2025-02)

• Benchmarked lightweight LLMs/MLLMs with prompt engineering, selecting a model on a quality–latency–memory trade-off; used GitHub Copilot with an automated evaluation harness and PyTest regression checks to validate generated outputs before integration.

Data Science Intern at Viettel AI (2024-05 – 2024-08)

• Built Python and SQL data pipelines over 1M+ records with feature engineering via SQL joins, window functions, and aggregations; ran A/B experiments with causal-inference methods and presented results to non-technical stakeholders.

Software Engineer Intern at YooLife (2024-01 – 2024-04)

• Shipped Python/PostgreSQL backend features (+30% system performance); collaborated with 13 developers across 50+ pull requests with CI checks.

Bachelor of Computing in Computer Science – Nanyang Technological University Singapore (2027-05)