Data Engineer - Purchasing Power Hybrid - Atlanta, GA

Position: Data Engineer - Purchasing Power (Open to Relocation | Hybrid - Atlanta, GA)
Data Engineer - (Purchasing Power) | Hybrid - Atlanta, GA) page is loaded## Data Engineer - (Purchasing Power) | Hybrid - Atlanta, GA) locations:
Atlanta, GAtime type:
Full time posted on:
Posted Yesterday job requisition :
JR101560
** Progressive Leasing
** is a leading provider of in-store and e-commerce lease-to-own solutions. With more than 20 years in Fin Tech, we’ve grown from start-up to industry leader by innovating, simplifying, and valuing people. We are a subsidiary of PROG Holdings (NYSE: PRG), a Fin Tech holding company with three business segments:
Progressive Leasing, Purchasing Power (a leading employee purchase program for consumer products and services using payroll deduction), and Four, a Buy Now Pay Later (BNPL) platform.

Purchasing Power is a leading employee purchase program that helps people buy the products and services they need through the convenience of payroll deduction. As part of PROG Holdings (NYSE: PRG), a Fin Tech holding company with more than 20 years of experience, we’re focused on building simple, responsible financial solutions that put people first. PROG Holdings’ portfolio includes Progressive Leasing, a market leader in lease‐to‐own solutions, Purchasing Power, and Four, a Buy Now Pay Later (BNPL) platform — all united by a commitment to innovation, access, and meaningful impact.

We’re looking for a
** Data Engineer
** to support the development and operation of our enterprise data platform. This role is highly tactical and execution‐focused, contributing directly to the reliability, scalability, and performance of our AWS‐based data ecosystem.

You’ll work closely with the Senior Director of Data Engineering and platform team to design, build, and maintain streaming and batch data pipelines, supporting real‐time ingestion, transformation, and delivery into analytics and reporting systems. This is a great opportunity for someone who enjoys working in distributed systems and wants to have a direct impact on how data is delivered across the business.
** WHAT YOU’LL WORK ON
**** Data Pipeline Development
*** Develop and maintain streaming and batch data pipelines using Kafka, Spark, and related technologies
* Implement ingestion pipelines using Kafka Connect and CDC patterns
* Build transformation and enrichment processes using Spark and Py Spark
* Ensure reliable data delivery to downstream platforms including Greenplum, Elastic, S3, and analytics tools
** Streaming Platform Support
*** Support Kafka topic configuration, partitioning strategies, and consumer group management
* Assist with schema registration and schema evolution practices
* Troubleshoot streaming pipeline issues and optimize performance
* Help maintain data integrity and reliability across distributed systems
** Data Processing & Transformation
*** Implement business logic and transformations within Spark processing frameworks
* Develop and maintain Airflow DAGs (or equivalent orchestration workflows)
* Build lookup and enrichment logic for streaming and batch pipelines
* Ensure data quality through validation, monitoring, and alerting practices
** Platform Operations
*** Monitor pipeline performance, failures, and data latency
* Assist with observability and monitoring using tools such as Elastic and Kibana
* Support incident resolution and root‐cause analysis for data pipeline issues
* Contribute to system performance tuning and platform optimization
** Collaboration
* ** Work closely with the Data Engineering Manager to implement platform architecture
* Partner with analytics and reporting teams to support BI and data delivery needs
* Assist with evolving platform integrations and modernization initiatives
** WHAT YOU BRING
*** 3–5+ years of experience in data engineering or distributed data systems
* Hands‐on experience building and maintaining pipelines using Spark / Py Spark
* Experience working with Kafka or other streaming platforms
* Strong SQL skills and experience with data transformation
* Experience with data orchestration tools such as Apache Airflow
* Familiarity with AWS‐based data environments
* Strong troubleshooting and debugging skills for data pipelines
* Curiosity, adaptability, and comfort working in…