Data Engineer: AWS, Databricks & PySpark Pipelines

REPAY; Arizona; On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

100% health premiums covered

401(k) employer match

Employee stock purchase plan

Annual bonus program

Job summary

REPAY is seeking a Data Engineer to design, build, and maintain scalable, cloud-based data pipelines and data models. You will optimize PySpark/SQL workloads, work with Databricks and AWS, and partner with BI, Product, and Engineering teams to deliver reliable data solutions.

The role requires 3–5 years in data engineering, strong Python/SQL skills, and experience with CI/CD and data warehousing concepts. Join a fast-growing fintech with a strong culture and career growth opportunities.

Qualifications

• Undergraduate or Masters' degree in Computer Science, Statistics, or Analytics.
• Minimum of 3-5 years of experience in Data Engineering, preferably with AWS-based cloud data platforms.
• Hands‑on experience building, maintaining, and supporting cloud-based data pipelines.
• Strong knowledge of PySpark, preferably on the Databricks platform.
• Hands‑on experience with Databricks.
• Strong proficiency in SQL, including query optimization.
• Strong proficiency in Python.
• Strong knowledge of data modeling, data warehousing, ETL/ELT, and analytics concepts.
• Experience with CI/CD practices, automated deployment processes, unit testing, and code quality standards.
• Experience troubleshooting, monitoring, and supporting production data pipelines.
• Experience documenting technical solutions, data flows, and pipeline logic.

Responsibilities

• Design, build, and maintain scalable, reliable cloud-based data pipelines and data infrastructure.
• Deliver high-quality data models and curated datasets for analytics and BI.
• Optimize Spark, PySpark, and SQL workloads for performance and cost.
• Support production data pipelines via monitoring and incident resolution.
• Implement CI/CD, automated deployments, and unit testing for data workflows.
• Collaborate with BI, Product, Engineering, Data teams to translate requirements into scalable data solutions.
• Document data flows, pipeline logic, and operational processes for maintainability.
• Build data models for structured, semi-structured, and NoSQL data.

Skills

PySpark

SQL

Python

Databricks

AWS

CI/CD

Data Modeling

Data Warehousing

ETL/ELT

Spark

Education

Bachelor's or Master's in Computer Science, Statistics, or Analytics

Tools

Databricks

AWS

Spark

Kafka/Kinesis

Power BI

Job description

REPAY is seeking a Data Engineer to design, build, and maintain scalable, cloud-based data pipelines and data models. You will optimize PySpark/SQL workloads, work with Databricks and AWS, and partner with BI, Product, and Engineering teams to deliver reliable data solutions.

The role requires 3–5 years in data engineering, strong Python/SQL skills, and experience with CI/CD and data warehousing concepts. Join a fast-growing fintech with a strong culture and career growth opportunities.