Senior Data Engineer

Role overview

Build customer-facing data products for businesses operating in the single-family home market, working closely with data science and product teams. The data engineering work is part of the product itself: reliable, high-quality datasets should help customers make decisions across areas such as underwriting, leasing, and vendor management. You will also help shape the data platform and establish engineering practices.

Responsibilities

- Design durable data models that represent residential real estate concepts clearly and consistently. - Build dependable workflows that generate and maintain useful data assets. - Contribute to the architecture and evolution of the data platform. - Set data engineering standards and practices that support quality and reliability. - Partner with data science and product colleagues to deliver data products for customer use. - Develop expertise in the real estate domain and apply it to data modeling and product decisions.

Requirements

- 6+ years of experience in data engineering or software engineering. - Strong background in data architecture, data modeling, and building data pipelines at scale. - Proficiency in SQL, Python, and/or Spark. - Experience with cloud data warehouses such as Snowflake, Redshift, or BigQuery. - Experience scheduling and operating batch data processing workflows.

Nice to have

Experience with workflow orchestration tools such as Airflow, Prefect, or Dagster; warehouse architecture or change data capture modeling; extraction from public or semi-structured sources; AI/ML platforms; or data infrastructure using Terraform, Docker, and cloud services.