Full-Stack Software Engineer (Data Pipelines)

Job Description Job Summary: Develop and maintain features across full-stack Node.js web application supporting global events team. Handle front-end components, back-end APIs, data layer integrations, and scheduled data pipelines. Contract position with high hourly pay. Essential Functions and Responsibilities:

• Develop and maintain features across full-stack Node.js web application, including front-end components, back-end APIs, and data layer integrations.
• Work with tables and write SQL queries to support data retrieval, transformation, and reporting needs.
• Build, maintain, and debug Python-based data pipelines running as scheduled jobs for data preprocessing and ingestion.
• Integrate and work with Jira APIs and data exports to support security risk workflows.
• Use CLI to manage jobs, clusters, and deployments.
• Deploy changes through staging-to-production workflow: build deploy to staging test promote to prod.
• Leverage agentic engineering tools to accelerate development and navigate unfamiliar codebase.
• Collaborate closely with team via Slack and participate in regular syncs, code reviews, and prioritization discussions.
• Contribute to reducing technical debt in existing data pipelines while supporting new feature development.

• Demonstrated experience with full-stack web development using Node.js or equivalent back-end frameworks.
• Comfort working with SQL and data-heavy applications; ability to read, write, and debug queries against large structured datasets.
• Experience with Python scripting or notebook-based data workflows.
• Familiarity with CLI-based developer workflows and cloud data platforms.

Functional Skills:

• Ability to ramp up quickly on existing codebase using AI-assisted development tools.
• Experience integrating APIs like Jira for security risk workflows.
• Behavioral Skills:
• Strong communication skills and experience working in collaborative, async-heavy team environments.

Nice to Have:

• Experience with lakehouse or data warehouse platforms.
• Familiarity with Jira’s data model or API.
• Background in security, GRC, or risk management domains.
• High proficiency with AI engineering workflows.