Muhammad Rizki Afdolli

I am a final year Computer Science student at Bina Nusantara University with a 3.58 GPA and a strong interest in data and software engineering. I enjoy solving real problems, delivering clear action items, and building products that matter. Across my internship experiences, I have built observability tooling, implemented end-to-end data quality checks, and contributed to large-scale pipeline infrastructure.

I am particularly drawn to roles at the intersection of AI and client-facing engineering — where data systems meet intelligent automation and direct stakeholder impact. These experiences strengthened my technical skills and my ability to translate complex requirements into practical solutions, making me well prepared to contribute in data, AI, or client engineering roles.

Data Quality Engineer Intern at DANA (PT Espay Debit Indonesia Koe) (2026-02 – Present)

• Built an end-to-end Airflow observability dashboard leveraging CDC-replicated metadata in MaxCompute, enabling real-time monitoring of DAG runs, task instances, and SLA misses to improve pipeline visibility across the data platform.
• Designed and implemented data quality completeness checks comparing composite keys between MySQL source tables and MaxCompute destination tables, catching data drift early and reducing undetected data loss incidents.
• Navigated ODPS-specific SQL quirks including CDC NULL representation and UNIX_TIMESTAMP compatibility flags, delivering reliable deduplication logic via ROW_NUMBER() on CDC operation timestamps across high-volume pipeline tables.
• Collaborated with stakeholders to understand data pipeline behavior including Flink CDC changelog semantics, upsert patterns, and snapshot internals, translating technical findings into actionable data quality improvements.

Data Engineer at 99 Group (99.co | Rumah123 | SRX ) (2025-02 – 2026-02)

• Collaborated with cross-functional teams to understand operational challenges and built Data Quality Checks for MySQL and Big Query pipelines using Airflow, improving incident response time by 50%.
• Designed and delivered an end-to-end Big Query usage data mart and cost monitoring dashboards that supported data-driven decision making and reduced quarterly spend by 20 percent.
• Initiated and led a proof of concept for a data lineage and governance tool to address debugging pain points in complex data marts and dashboard dependencies, enabling teams to diagnose issues faster and with greater context.
• Built and maintained end-to-end data pipelines using Airflow and dbt within a Kubernetes environment, integrating MySQL, NoSQL, data lake, and data warehouse systems to deliver reliable, well-structured data products for analysts and internal stakeholders.
• Developed scrapers and automated data processes used across business units, demonstrating the ability to translate requirements into practical technical solutions.
• Integrated an AI-assisted diagnostic agent into Airflow to automatically summarise task failures, identify likely root causes, and provide recommended fixes in Slack, improving engineering productivity and cross-team communication.
• Maintained and enhanced automated web crawlers and scrapers, optimizing crawling logic and scheduling to improve data collection time by 30% while expanding coverage across additional sources and endpoints.

Bachelor of Engineering in Computer Science; Minors in Data Science – Bina Nusantara University (2026-08)

Science and Technology – SMA Negeri 1 Cirebon (2019-01 – 2022-04)