Global Payments Inc. · 6 hours ago

Principal Software Engineer, Data Engineering

Charlotte, NC

Full-time

Remote

Lead/Staff

8+ years exp

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Responsibilities

Design and implement robust data models, leveraging dimensional modeling principles to structure data for performance, usability, and scalability in reporting and analytics.

Lead the development of efficient ETL processes, data pipelines, and workflows to transform, integrate, and load data from multiple sources into the data warehouse.

Architect and optimize data warehousing solutions that support high query performance and can scale with increasing data volume and complexity.

Develop and enforce data quality standards, including validation, transformation, and cleansing rules to ensure data accuracy and consistency across the organization.

Perform detailed performance tuning of ETL processes and query optimization to improve data processing speeds and reduce latency in data access.

Mentor other engineers, guiding them on best practices for data engineering, data warehousing, and dimensional modeling.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data Architecture & ModelingETL & Data PipelinesData WarehousingDimensional ModelingSQL ProficiencyData Governance & QualityPerformance TuningETL FrameworksProgramming KnowledgeMentorship & LeadershipBig Data Technologies

Required

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

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.