About the Role
Title: Principal Software Engineer, Data Engineering
Location: Remote USA
Full time
job requisition id
R0055861
Job Description:
Every day, Global Payments makes it possible for millions of people to move money between buyers and sellers using our payments solutions for credit, debit, prepaid and merchant services. Our worldwide team helps over 3 million companies, more than 1,300 financial institutions and over 600 million cardholders grow with confidence and achieve amazing results. We are driven by our passion for success and we are proud to deliver best-in-class payment technology and software solutions. Join our dynamic team and make your mark on the payments technology landscape of tomorrow.
Summary of This Role
As a Principal Software Engineer in Data Engineering, you will lead the design, implementation, and optimization of our data infrastructure, including data warehousing, ETL processes, and data pipelines. Drawing from established best practices in dimensional modeling, you will help architect scalable, high-performance solutions that ensure data accuracy, reliability, and accessibility for AI/ML, analytics, and business intelligence (BI) initiatives.
What Are We Looking For in This Role?
Minimum Qualifications
- 4-year degree in Computer Science or Engineering concentration, combination of relevant training and/or experience in lieu of degree acceptable
- 8+ years of experience in software development.
- Data Architecture & Modeling: Design and implement robust data models, leveraging dimensional modeling principles to structure data for performance, usability, and scalability in reporting and analytics.
- ETL & Data Pipelines: Lead the development of efficient ETL processes, data pipelines, and workflows to transform, integrate, and load data from multiple sources into the data warehouse.
- Data Warehousing: Architect and optimize data warehousing solutions that support high query performance and can scale with increasing data volume and complexity.
- Data Governance & Quality: Develop and enforce data quality standards, including validation, transformation, and cleansing rules to ensure data accuracy and consistency across the organization.
- Performance Tuning: Perform detailed performance tuning of ETL processes and query optimization to improve data processing speeds and reduce latency in data access.
- Mentorship & Leadership: Mentor other engineers, guiding them on best practices for data engineering, data warehousing, and dimensional modeling.
Preferred Qualifications
- Extensive Knowledge of Dimensional Modeling: Expertise in designing star schemas, snowflake schemas, and other dimensional models per Kimball methodology.
- Advanced Data Engineering Skills: Proven experience with ETL frameworks, data pipeline design, and data warehousing technologies such as Snowflake, Redshift, BigQuery, or similar platforms.
- SQL Proficiency: Deep understanding of SQL, query optimization, and performance tuning.
- Programming Knowledge: Strong proficiency in languages such as Python, Java, or Scala for data processing and pipeline development.
- Analytical Thinking: Exceptional problem-solving skills, with the ability to translate complex data requirements into efficient data models and processes.
- Experience with Big Data: Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.