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Role Overview
- The Full Stack Engineer will be responsible for developing an automated property valuation system that pulls in public data, calculates property values, and integrates with Salesforce.
- The role focuses on integrating real-time data, building algorithms, and automating the valuation process to ensure fast, accurate results.
Responsibilities
- System Development: Build and develop an automated property valuation system that pulls in public data (e.g., tax data, real estate sites like Zillow, PropStream) and calculates property values using set metrics.
- Salesforce Integration: Integrate backend algorithms into Salesforce to automate the property evaluation process based on user inputs.
- Database Management: Work with various public and paid data sources to obtain relevant property information and ensure the system can process this data in real-time.
- API Integrations: Develop and maintain APIs that pull information from external real estate databases such as tax records, MLS listings, and Zillow.
- Automation & Algorithms: Build algorithms that adjust property pricing based on input data (e.g., square footage, neighborhood statistics, market trends) and return results instantly to users.
- System Optimization: Continuously monitor and improve the performance of the system to ensure it delivers fast and accurate property valuations with minimal delay.
- Collaboration: Work with the marketing and sales teams to refine the automation process and enhance lead conversion.
Must Have
- Strong Full Stack Development Skills: Experience in both front-end and back-end development, including building scalable web applications.
- Experience with Salesforce: Must have knowledge of integrating algorithms and automations into Salesforce.
- Expert in Algorithms & Automation: Proficiency in developing algorithms that interact with real-time data and public information.
- Proficiency in Relevant Technologies: Strong skills in languages like JavaScript, Python, PHP, Ruby, or similar for full-stack development.
- Real Estate Data Understanding: Familiarity with real estate valuation models, market trends, and public databases (MLS, Zillow, PropStream) is a plus.
- Experience with Data-Driven Applications: Experience developing applications based on large sets of data, particularly related to finance or real estate.
- Problem-Solving Skills: Ability to troubleshoot issues with data sources and algorithm outputs, ensuring smooth operations.
Nice To Have
- Real Estate Industry Experience: Knowledge or experience working with iBuyer platforms, real estate valuation, or similar industries.
- Experience with AI/ML: Familiarity with applying AI or machine learning to automate data processing and prediction models.
- Backend Database Experience: Working knowledge of SQL, MongoDB, or similar technologies for handling large data sets.
Method of Application
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