Staff Software Engineer (Data Platform)

Role Overview

Staff Software Engineer on the Data Platform team at Built Technologies. You’ll lead design and delivery of application-facing data products, build full-stack customer experiences, and partner with cross-functional teams to integrate data products into application surfaces and customer workflows.

Key Missions

• Lead the design and delivery of Built’s application-facing data products platform, including:
  • Product surfaces and frontend flows
  • Backend services and APIs
  • Reusable patterns and service/product architecture
• Build full-stack customer experiences using TypeScript, React, Node.js, Python, and related technologies, and help convert data science prototypes into production-grade experiences.
• Collaborate across Built to integrate data products into application surfaces, platform capabilities, agents, and customer workflows, using customer signals to guide engineering decisions.

Requirements

• Python experience (or demonstrated ability to work effectively in Python-based systems)
• Strong technical communication (e.g., design docs, architecture discussions, tradeoff analysis)
• Bias toward customer value and strong product judgment
• Experience designing:
  • APIs and service boundaries
  • Reusable application patterns
  • Production backend systems
• Staff-level experience leading ambiguous, customer-facing initiatives from idea through production
• Ability to write high-quality, maintainable code with instincts for:
  • Testing
  • Readability
  • Observability
  • Operational ownership
• Collaborative leadership: challenge product direction constructively and mentor engineers
• Strong experience with TypeScript, Node.js, React, and modern web application architecture
• Full-stack experience with backend-leaning product engineering depth

Nice-to-Haves

• Data-heavy product experience (analytics, reporting workflows, benchmarking tools, dashboards, decision-support)
• Experience with AI/agentic product experiences
• Experience working with data/analytics engineering and data scientists to productionize prototypes
• Familiarity with data platform technologies such as Snowflake, dbt, Kafka, Flink, Materialize
• Fintech or other trust/correctness-sensitive domains (lending, banking, real estate, compliance-heavy SaaS)
• Experience with instrumentation and growth loops (activation metrics, experimentation, usage-based iteration)
• Experience mentoring engineers from adjacent disciplines into stronger software engineering practices