RevenueBase

• Fix the Financial Data Pipeline — Audit and rebuild how data flows between Stripe, HubSpot, and QuickBooks • Build Internal Dashboards & Reporting — Create a reporting layer the entire team can rely on • Own Funnel Analysis — Build the reporting to track both funnels independently • Own the Monthly Close — Direct Pilot on GL coding • Solve Revenue Recognition — Navigate the complexity of ASC 606 • Build Strategic Models — Create and maintain rolling cash flow forecasts • Prepare for Series A — Build and maintain the financial model and data room • Manage the Basics — Oversee accounts receivable, accounts payable, and GAAP-compliant financial statements

• Own the "first successful search" — every new customer's activation milestone. Get them there, fast. This is the most important thing you do. • Own customer health across all accounts. Know which customers are getting value, which are quiet, and which are at risk — before anyone asks. • Drive expansion and cross-sell. As we ship new API surface area (verification, enrichment, discovery, MCP), identify which customers need what and run the expansion conversation. • Run onboarding at scale. 3-5 new customers per month today, scaling to 10+. Make onboarding light, fast, and reliably successful. • Be the voice of the customer inside RevenueBase. Sit on top of every Slack channel, every support request, every integration conversation, and tell product and engineering what customers actually need. • Build the function. Write the playbooks, the health scoring, the expansion motion, and the onboarding framework — then rewrite them when they stop working.

• Design, build, and maintain scalable backend services using Python and FastAPI. • Develop and optimize high-performance RESTful APIs powering AI agents and GTM workflows. • Architect and maintain cloud-native infrastructure (compute, storage, networking). • Build reliable data pipelines and services that process, validate, and serve large B2B datasets. • Ensure system scalability, observability, and fault tolerance. • Own backend features end-to-end — from design and implementation to deployment and monitoring. • Collaborate closely with frontend and data engineers to ensure clean API contracts and reliable data flow. • Contribute to architectural decisions, code reviews, and engineering best practices. • Continuously improve performance, security, and maintainability across backend systems.

• Learn the RevenueBase platform, shadow customer calls, and close your first deal. Understand our ICP, competitive positioning, and what makes customers say yes. • Own your full pipeline: prospecting, demos, negotiations, and closes. Identify repeatable patterns in what's working and feed insights back to product and marketing. Begin engaging with partnership opportunities. • Hit quota, expand existing accounts, and contribute to the sales playbook. Actively work partnership deals; building pipeline and closing reseller agreements with companies who distribute RevenueBase data.

• Build and maintain production-ready data pipelines using DBT, Snowflake, and modern orchestration tools. • Own data engineering features end-to-end, from implementation through optimization and deployment. • Fix and improve existing pipelines - identify bottlenecks, resolve issues, and enhance performance. • Drive automation initiatives across the data stack to accelerate delivery and reduce manual interventions. • Provide 2nd line support for B2B customers - investigate data issues, clarify edge cases, and ensure customers can trust their data. • Design and implement new data import pipelines as we expand our data source coverage. • Implement data quality improvements - validation, monitoring, and testing to ensure reliable, accurate data delivery. • Contribute to code reviews, architectural discussions, and data engineering best practices.

• Lead the initiative to reduce developer onboarding time to <5 minutes. • Ensure operational and workflow support with copy-pasteable code snippets. • Write foundational guides for customers configuring tools like Snowflake and S3. • Ensure documentation is indexed for search and LLM queries.

• Build and maintain high-quality, production-ready web interfaces using React and Next.js. • Own frontend features end-to-end, from implementation through optimization and release. • Translate complex data workflows into intuitive, performant, and responsive user experiences. • Work closely with backend engineers to integrate APIs and ensure reliable data flow. • Contribute to code reviews, architectural discussions, and engineering best practices. • Continuously improve performance, reliability, and maintainability across the web platform. • Help raise the overall engineering bar as the product and team scale.

• Design the New Web App End-to-End — Take our existing POCs and shape them into a polished, production-ready product experience. Onboarding, data browsing, self-serve purchasing, API key management, usage dashboards — you own all of it. • Build the Information Architecture — Organize complex data products so technical users find what they need fast. Our platform has multiple data types, delivery methods, and pricing models. Make it feel simple. • Design PLG & Developer Flows — Signup, activation, freemium-to-paid conversion, self-serve purchasing, and API onboarding. You understand what makes a developer try something for 5 more minutes vs. bounce. • Prioritize Ruthlessly — Know what matters to CTOs and engineers and cut what doesn't. Developers hate clutter, unnecessary steps, and marketing fluff in product UI. Design accordingly. • Design for Dual Personas — The primary user is technical (CTOs, developers, data engineers). The secondary user is revenue operations. Build experiences that serve both without diluting either. • Collaborate on the Roadmap — Work with product and engineering to translate a multi-phase roadmap into tangible design milestones. Balance speed with quality as we ship iteratively.

• Architect Distributed Stealth Systems: Design and deploy horizontally scalable scraping nodes (Go or Python/Asyncio) on AWS Lambda/Fargate or Kubernetes to maintain massive throughput. • Hidden API Discovery: Use Charles Proxy, Fiddler, or Burp Suite to map out undocumented internal APIs and mobile backend endpoints—finding the "backdoor" pathways that bypass heavy front-end obfuscation. • Fingerprint Evasion: Implement advanced techniques to bypass enterprise-grade bot detection, specifically focusing on TLS fingerprinting (JA3), HTTP/2 headers, and browser fingerprinting evasion. • Orchestrate Massive Infrastructure: Manage large-scale residential and mobile proxy pools to ensure a sustained rate of 1M+ requests per hour while optimizing for cost and success rate. • Build for Resilience: Develop real-time monitoring to track success rates and "burn" rates of proxy infrastructure, ensuring the system can recover automatically when targets update their defenses.

• Design and build data-driven tools that operate on large datasets stored in S3 and Snowflake • Implement pipelines that: • Extract specific columns or datasets from Snowflake • Generate vector embeddings via APIs such as OpenAI • Store and manage embeddings in vector databases like Pinecone • Enable semantic search and similarity-based retrieval • Develop enrichment workflows that: • Query structured data • Use LLM APIs to generate new derived columns • Write enriched results back into Snowflake • Build reusable internal services and SDKs around embedding generation, prompt orchestration, and data augmentation • Optimize performance and cost across AWS infrastructure • Work closely with product and data teams to turn use cases into scalable engineering solutions • Ensure reliability, observability, and maintainability of AI-powered pipelines