Data Engineer (India)

Resident Interface; Pune District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Resident Interface is looking for a Data Engineer to build and maintain data pipelines supporting their analytics platform. This role is critical for transforming how the rental housing industry manages data. You'll partner closely with analysts and developers to ensure data quality and reliability.

Key qualifications include 4–6 years of experience, strong Python and SQL skills, and hands-on experience with AWS services. Join us to shape the future of delinquency management!

Qualifications

• 4–6+ years of experience in data engineering or related roles.
• Strong proficiency in Python, including Pandas and PySpark.
• Advanced SQL skills with experience in complex transformations.

Responsibilities

• Build and maintain scalable data pipelines and ETL processes.
• Develop workflows using Python, PySpark, and SQL.
• Integrate systems using REST APIs and Python frameworks.

Skills

Python

SQL

PySpark

Data pipeline management

AWS (S3, Glue, Redshift)

Tools

PostgreSQL

MySQL

Git

Job description

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.

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.