About Resident Interface
Resident Interface is the industry leader in delinquency management for the rental housing market. Through our brands Possession Partner (Evictions), Resident Advocate (Pre-Collections), and Hunter Warfield (Collections) we deliver a unified platform that helps property owners and managers recover revenue, stay compliant, and protect their communities.
With over 40 years of experience, $billions recovered nationwide, and operations across all 50 states, Resident Interface combines technology, transparency, and expertise to transform the way property owners manage delinquencies from the first missed payment to final resolution.
Learn more at www.residentinterface.com
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 efficient, 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 collaborative development practices
What You Bring
- 4–6+ years of experience in data engineering or related roles
- Strong proficiency in Python, including Pandas and PySpark
- Advanced SQL skills (core to the role), including complex transformations, performance optimization, and large-scale data processing
- Experience with relational databases such as PostgreSQL and/or MySQL
- Hands-on experience building and maintaining data pipelines and ETL workflows
- Experience working with AWS services such as S3, Glue, and Redshift
- Familiarity with REST APIs and Python API frameworks (e.g., FastAPI, Flask)
- Strong experience with data cleaning, transformation, and validation
- Strong understanding of data modeling concepts (e.g., normalization, dimensional modeling) and their application in analytics environments
- Experience using Git for version control and collaborative development
- Ability to work with large, complex datasets in a fast-paced environment
Bonus Points For
- Familiarity with workflow orchestration tools (e.g., Airflow)
- Experience building or contributing to new data platforms or major system overhauls
- Exposure to fintech, proptech, legaltech, or collections-related data
- Experience optimizing data pipelines for performance and cost in cloud environments
Why This Role Is Different
Build the Foundation – You’ll help architect the pipelines and data structures powering a next-generation analytics platform
High Impact, Low Bureaucracy – Work directly with decision-makers and see your work immediately used across the business
Tight Analyst Partnership – Your work directly enables faster, better insights for both internal teams and external clients
Platform-Level Ownership – This isn’t maintenance work—you’ll help define how data engineering is done here
Team & Impact
You’ll work closely with a growing team of analysts and developers across India and the U.S., helping establish the foundation for scalable, high-quality data across the organization.
