About the Role
We’re on a mission to transform how the rental housing industry understands and manages bad debt—and we’re building a brand-new analytics platform to do it. As a Data Engineer, you’ll play a critical role in making that vision a reality.
This role sits at the foundation of our data platform. You’ll be responsible for building and maintaining the pipelines, data structures, and integrations that power our analytics, reporting, and client-facing tools.
You won’t just move data—you’ll shape how it flows, how it’s structured, and how it’s trusted across the organization. You’ll work closely with analysts, developers, and product stakeholders to ensure our data is clean, scalable, and ready to drive decision-making.
We’re looking for a hands-on engineer who enjoys solving complex data challenges, building reliable systems, and enabling others to do their best work with data.

What You’ll Do
Build and maintain scalable data pipelines and ETL processes supporting our analytics platform
Develop data workflows using Python, PySpark,



and SQL across multiple data sources
Design and implement data transformations to ensure clean, reliable, and analytics-ready datasets
Integrate internal and external systems using REST APIs and Python-based frameworks
Manage and optimize data storage and processing in AWS (S3, Glue, Redshift)
Write effective, production-grade SQL for data extraction, transformation, and performance optimization
Partner with analysts to ensure datasets are structured and usable for reporting and analytics
Contribute to data modeling efforts to ensure scalable and intuitive data structures
Monitor and troubleshoot data pipelines, ensuring reliability and data quality
Maintain version-controlled codebases using Git and support cooperative development practices

What You Bring
4–6+ years of experience in data engineering or related roles
Robust proficiency in Python, including Pandas and PySpark
Advanced SQL skills (core to

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