Your most recent job title indicates a software engineering role.

Your most recent job title indicates mid-level seniority, one step above the required entry-level.

Your resume has 4.9 years of experience

The resume clearly shows software engineering experience through multiple roles as Full-stack Software Engineer and Software Engineer, plus substantial implementation work across APIs, web apps, and codebase contributions.

Python is explicitly listed in the skills section, so the resume clearly contains this language in the relevant software engineering context.

Java is explicitly listed in skills and also used in a software engineering project/experience, so this is a clear match.

The resume does not mention Ruby anywhere in skills, experience, or projects.

The resume suggests some scale-oriented work, such as a REST API managing over 10 million records and a web application analyzing over 500,000 repositories, but it does not explicitly demonstrate system scalability design or engineering of scalable systems as a core concept.

The resume includes building and developing systems and applications, but it does not specifically show system design work in the role-relevant sense of architecture or design discussions/documents.

There is no explicit mention of diagnosing, handling, or resolving production issues in the resume.

SQL is explicitly listed in skills, including SQL (Postgres), and PostgreSQL is used in experience, making this a clear match.

The resume shows strong visualization-related work, including data visualization tools/libraries and a web application with commit heatmaps, contributor analytics, and interactive dashboards. This is similar to visualization software in the intended context, though not explicitly productized visualization software.

The resume does not mention financial risk, regulatory risk, fraud, compliance, AML, or related risk-platform work. The experience is general software engineering and data visualization, not risk-domain engineering.

There are clear signs of scalable engineering experience, including a REST API managing over 10 million records and a full-stack application analyzing over 500,000 GitHub repositories, which suggests building systems that handle large data volumes.

The resume shows system-building experience across APIs, web applications, and data pipelines, but it does not explicitly reference formal system design work or architecture ownership. This is a related concept rather than a clear direct match.

The resume mentions 60+ bug fixes and maintaining high test coverage, which implies issue handling in an engineering environment, but it does not clearly show production incident response or resolution of live production issues.

SQL is explicitly listed in the skills section, and PostgreSQL is used in multiple projects and work experiences, showing direct experience with SQL.

The resume strongly shows data visualization work, including interactive dashboards, commit heatmaps, contributor analytics, and a hero message of Full-Stack SW Engineer | Data Visualization. This matches visualization software in a relevant way.

The resume includes analytics-oriented work such as repository analysis, clustering, heatmaps, and contributor analytics, which indicates data-informed investigation and exploration, though not explicitly framed as investigative or risk-analysis work.

The resume shows experience developing and managing software platforms, including REST APIs, full-stack web applications, and visualization tools. However, it does not mention financial risk, regulatory risk, compliance-focused work, or explicitly balancing such risk with user experience.

The resume includes multiple examples of building scalable engineering solutions, such as a REST API for over 10 million records and a full-stack application analyzing over 500,000 GitHub repositories. This indicates the ability to solve problems with scalable technical solutions, though the resume does not explicitly state 'business challenges.'

The resume does not mention cross-functional collaboration with product, policy, legal, operations, or data science teams. It does show engineering work, but there is no explicit evidence of partnering with these specific stakeholder groups.

The resume shows full-stack engineering experience with REST APIs, Flask/React/PostgreSQL/Docker applications, and maintenance work such as 60+ bug fixes and high test coverage. However, it does not explicitly mention production incident diagnosis, cross-service troubleshooting, or stack-layer issue resolution in an operations/support context.

The resume includes contributions such as maintaining high test coverage, using Git, Docker, TravisCI, and building applications with modern frameworks, which suggests solid engineering practices and tooling use. Still, it does not explicitly state process improvement, engineering standards ownership, or tooling optimization.

There is no explicit evidence of risk analysis, emerging risk pattern identification, or mitigation work in the resume. The closest related experience is debugging and bug fixing, but that is not the same as risk assessment or proactive risk mitigation.