Nicolas Soto

Software Engineer with about 5 years of experience. Work centers on Postgres and SQL migrations to keep financial datasets consistent, secure, and usable for downstream analytics and ML-ready pipelines. Built resilient data ingestion workflows with strong authentication and careful normalization to support complex banking data. Known for high agency, shipping under fast-paced deadlines, and maintaining flat structure communication across stakeholders.

Experience includes designing canonical models, developing feature extraction pipelines, and shaping production systems that support automated financial insights. Scope has stayed reliably practical, from schema to services to operational monitoring across income categorization and anomaly detection use cases.

Software Engineer at FIS (2021-06 – Present)

Engineered backend data platform capabilities for financial products, focusing on end-to-end ownership from ingest to serving. Built resilient data ingestion and data normalization pipelines for complex banking data and tax transcripts. Designed core platform infrastructure with APIs and SDKs, while supporting authentication, webhooks, and rate limiting for secure automation.

Shipped ML-ready pipelines, canonical models, income categorization, and anomaly detection to power automated financial insights.

• Architected the infrastructure for data ingestion and canonical models, ensuring end-to-end ownership across banking data and tax transcripts while improving reliability by 20%.
• Design and operate resilient data ingestion pipelines with SQL migrations, ensuring authentication and rate limiting stayed consistent across high-volume fintech events.
• Built ML-ready pipelines for feature extraction pipelines, shaping canonical models and ensuring income categorization data stayed normalized for downstream ML models.
• Productionize ML models by building APIs and SDKs around canonical models, enabling automated financial insights while supporting webhooks and scalable processing.

Software Engineer Intern at U.S. Department of Veterans Affairs (2020-05 – 2020-12)

Supported backend engineering for systems handling sensitive records, with a focus on data normalization, secure access patterns, and dependable automation. Contributed to SQL-focused schema updates and ingestion routines, improving how data moved through operational workflows and analytics-ready structures. Helped consume upstream outputs via APIs while ensuring correctness across normalization steps and productionization standards.

• Developed a data normalization pipeline with complex Postgres schema design, ensuring normalized records were consumed reliably by downstream services across automated workflows.
• Implemented SQL migrations and improved resilience for ingestion routines, ensuring authentication controls remained stable while reducing manual rework by 30 hours/month.
• Designed webhook-driven updates for operational automation, enabling timely ingestion and shaping anomaly detection-ready datasets for analysis.

Bachelor's degree in Computer Science – University of Central Florida (2017 – 2020)