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REPAY (“Realtime Electronic Payments” / NASDAQ TICKER: RPAY) is an established and fast-growing publicly traded financial technology and payment processing company headquartered in Atlanta, Georgia, with offices across the country. REPAY enables its customers to accept payments anytime, anywhere, and through any channel while providing a secure, seamless, and enjoyable payment experience for the end consumers. REPAY offers a comprehensive suite of electronic payment and funding solutions, including debit and credit card processing, ACH processing, Instant Funding, and electronic bill payment systems with full IVR, text, and mobile capabilities. The scalability of its products allows merchants of all sizes to add an instant arsenal of intelligent payment technology solutions to their businesses without significant development costs or infrastructure investments.

REPAY is looking for a Data Engineer to join our growing team. The Data Engineer is responsible for designing, building, optimizing, and maintaining scalable cloud-based data infrastructure and data pipelines that enable reliable data processing, analytics, reporting, and business intelligence capabilities. This role focuses on developing production‑grade data pipelines, data models, and ETL/ELT processes using modern data engineering tools and platforms, including AWS, Databricks, PySpark, SQL, and Python. The Data Engineer partners with BI, Product, Engineering, and client‑facing teams to ensure high-quality, well‑documented, and performance‑optimized data solutions that support business insights and operational decision‑making.

• Design, build, and maintain scalable, reliable cloud‑based data pipelines and data infrastructure.
• Deliver high‑quality data models and curated datasets that support analytics, reporting, and data‑driven decision‑making.
• Optimize Spark, PySpark, and SQL workloads to improve performance, reliability, cost efficiency, and scalability.
• Support production data pipelines through monitoring, troubleshooting, incident resolution, and continuous improvement.
• Implement data engineering standards, CI/CD practices, automated deployment processes, unit testing, and code quality expectations.
• Partner with BI, Product, Engineering, and client‑facing teams to translate business and reporting requirements into scalable data solutions.
• Document technical solutions, data flows, pipeline logic, and operational processes to support knowledge sharing and long‑term maintainability.
• Design, build, maintain, and optimize data pipelines using Python, SQL, PySpark, Databricks, and AWS‑based data services.
• Develop ETL/ELT processes that support data warehousing, analytics, reporting, and business intelligence use cases.
• Build and optimize Spark jobs, with a focus on performance, scalability, reliability, and efficient resource utilization.
• Design and implement data models for structured, semi‑structured, and NoSQL data where applicable.
• Implement CI/CD practices, automated deployments, unit tests, and code quality standards for data engineering workflows.
• Monitor, troubleshoot, and support production data pipelines, resolving issues and recommending improvements.
• Collaborate with BI Analysts, Product, Engineering, Data, and client‑facing teams to understand requirements and support reporting needs.
• Document technical solutions, data flows, pipeline logic, and operational processes.
• Share technical knowledge through documentation, mentorship, and team knowledge‑sharing sessions.
• Stay current with advancements in data engineering, cloud platforms, Spark, Databricks, data warehousing, and analytics technologies.
• Participate in client‑facing design sessions, technical presentations, workshops, or training as needed.
• Other duties as assigned.

• Required Undergraduate or Masters’ degree in Computer Science, Statistics, or Analytics.
• Minimum of 3–5 years of experience in Data Engineering, preferably working 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.
• Strong analytical and problem‑solving skills, with the ability to translate business requirements into scalable data solutions.
• Excellent written and verbal communication skills, including the ability to explain technical concepts to technical and non‑technical stakeholders.
• Ability to collaborate effectively across BI, Product, Engineering, Data, and client‑facing teams.
• Strong organizational skills and ability to manage multiple priorities in a fast‑paced environment.
• Proactive, ownership‑oriented mindset with the ability to work independently and drive solutions from design through production support.
• Professionalism and composure when supporting production issues or participating in client‑facing discussions.
• Preferred Apache Kafka experience.
• AWS Lambda experience.
• AWS Glue experience.
• MongoDB experience.
• Experience with streaming technologies such as Kafka or Kinesis.
• Terraform experience.
• Familiarity with an analytics/visualization platform such as Power BI or Tableau.

As the industry‑leading financial technology provider in the Consumer Finance and Business to Business spaces, we continue to set the standard for application development and delivery. In 2019, REPAY became a public company listed on the Nasdaq Stock Market (RPAY). For the past three consecutive years, we have placed on the ACG® Atlanta Georgia Fast 40, a list recognizing the top 40 fastest‑growing middle‑market companies in Georgia. REPAY’s leadership empowers each team member to make a difference and stretch to their fullest potential. Our dedication to frequent, transparent communication is shown with companywide meetings where our leaders share company vision and encourage employees to ask questions.

We offer it all: business to casual dress, great snacks & beverages, and open‑air collaborative team settings. REPAY has been certified as a Great Place to Work® company for 2017, 2018, 2019, 2020, 2021, and 2022. The REPAY team is fun, smart, collaborative, and truly enjoys working together. Making a difference in our local communities – we support several philanthropic initiatives every year to give back to our local communities. We are self‑driven, motivated professionals who do not require micro‑management to ensure we produce high quality and timely work.

We create highly sophisticated payment processing applications and are always pushing the boundaries of what is possible. We are constantly revolutionizing the industry by building on new ideas from clients and employees. We provide the resources necessary to ensure new innovations can develop quickly and with quality. We encourage continuing education, including professional conferences and events.

• We offer a comprehensive benefits package which includes 100% coverage of employee healthcare premiums and several free benefits, including life insurance, disability insurance, and work‑life balance resources.
• All benefits go into effect day one.
• We have a 401(k)-employer match and an Employee Stock Purchase Plan.
• REPAY employees are eligible to participate in our Annual Bonus Program.

REPATS core values are Excellence, Passion, Innovation, Respect, and Integrity.

REPAY is an Equal Opportunity Employer and we promote a company culture where diversity, equity and inclusion are central.

We are committed to build our teams and grow a company in which employees can succeed, regardless of race, color, national origin, sex, sexual orientation, gender identity or expression, transgender status, pregnancy, religion, age (40 and over), disability, service in the uniformed services, protected veteran status, genetic information, or any other classification protected by federal, state or local law.

We are interested in every qualified candidate who is eligible to work in the United States.

This position is not eligible for hire in California.

Additionally, we are not able to sponsor visas.