Founding Data Engineer (Pricing/Comps)

Accountabilities: Design and build scalable data pipelines and infrastructure supporting pricing and comparable-market data. Develop systems for collecting, ingesting, cleaning, transforming, and organizing data from relevant sources. Establish reliable data models and workflows that support accurate pricing analysis and comparable-data use cases. Build data infrastructure with scalability, reliability, maintainability, and data quality in mind. Collaborate closely with engineering and product teams to translate business and product requirements into effective data solutions. Identify opportunities to automate manual data processes and improve the efficiency of data operations. Establish monitoring, validation, and quality-control practices to ensure the accuracy and consistency of critical datasets. Help define the technical direction, architecture, and best practices for the data engineering function as an early member of the team. Take ownership of projects end-to-end, from technical design and implementation through deployment and ongoing improvement. Requirements: Professional experience in data engineering, analytics engineering, software engineering, or a closely related technical discipline. Strong experience designing and maintaining data pipelines, data models, and data infrastructure. Proficiency with SQL and a modern programming language such as Python. Experience working with structured and unstructured datasets and transforming raw data into reliable, usable information. Strong understanding of data architecture, ETL/ELT processes, data quality, and scalable data systems. Ability to work effectively in an early-stage or highly autonomous environment where requirements may evolve quickly. Strong problem-solving skills and a pragmatic approach to tackling ambiguous technical challenges. Excellent communication and collaboration skills, with the ability to work across technical and product functions. A strong sense of ownership, curiosity, and willingness to build systems from the ground up. Experience with cloud data platforms, orchestration tools, databases, APIs, web data collection, or data-intensive products is a plus. Benefits: Full-time employment. Fully remote work. Founding-level ownership and influence over the data engineering function. Opportunity to shape data architecture, infrastructure, and engineering practices from an early stage. Significant autonomy and direct impact on the development of the product and platform. Opportunity to work on challenging pricing and comparable-market data problems. Close collaboration with engineering and product stakeholders. Fast-moving environment with substantial opportunities for technical and professional growth.