Data Engineer

Description

Ria Money Transfer, a business segment of Euronet Worldwide, Inc. (NASDAQ: EEFT), delivers innovative financial services including fast, secure, and affordable global money transfers to millions of customers along with currency exchange, mobile top-up, bill payment and check cashing services, offering a reliable omnichannel experience. With over 600,000 locations in nearly 200 countries and territories, our purpose remains to open ways for a better everyday life.

We believe we can create a world in which people are empowered to build the life they dream of, no matter who they are or where they are. One customer, one family, one community at a time.

ROLES & RESPONSIBILITIES

• Design, build, and maintain scalable and reliable data pipelines for batch and real-time processing.
• Develop end-to-end data solutions, from data ingestion and transformation to storage and delivery for analytics and reporting.
• Build and optimize ETL/ELT processes to integrate data from multiple internal and external sources.
• Ensure the accuracy, consistency, reliability, and quality of data across pipelines and platforms.
• Design and maintain scalable data models and data storage solutions to support business and operational needs.
• Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and cost efficiency.
• Implement data validation, testing, and monitoring processes to identify and resolve data quality issues.
• Collaborate with Data Analysts, Business Intelligence teams, Software Engineers, and business stakeholders to understand data requirements and deliver scalable solutions.
• Support the development of datasets and data products used for reporting, analytics, and operational decision-making.
• Contribute to the definition and implementation of data engineering standards, best practices, and governance.
• Document data pipelines, data models, and technical processes to ensure maintainability and knowledge sharing.

POSITION REQUIREMENTS

• 4+ years of experience as a Data Engineer or in a similar data-focused engineering role.
• Strong proficiency in Python and SQL.
• Hands-on experience designing and building ETL/ELT pipelines.
• Experience working with large and complex datasets in both batch and real-time processing environments.
• Strong knowledge of data modeling, including relational and dimensional modeling concepts.
• Experience with cloud-based data platforms and services, preferably AWS.
• Experience with data warehouses and/or data lakes.
• Familiarity with distributed data processing technologies such as Apache Spark.
• Experience working with data orchestration and workflow management tools.
• Knowledge of data quality, validation, monitoring, and observability practices.
• Experience with version control and software development best practices.
• Strong problem-solving and analytical skills.
• Excellent written and verbal communication skills in English.

PREFERRED QUALIFICATIONS

• Experience with AWS data services such as S3, Glue, Redshift, EMR, Athena, Lambda, or Kinesis.
• Experience with data orchestration tools such as Apache Airflow.
• Familiarity with infrastructure as code and automation tools.
• Experience with streaming and event-driven architectures, such as Kafka or AWS Kinesis.
• Experience with modern data transformation tools such as dbt.
• Familiarity with containerization technologies such as Docker and Kubernetes.
• Experience working in a financial services, payments, fintech, or other highly regulated environment.
• Experience supporting data platforms used by multiple teams and stakeholders.