Senior Data Engineer, Finance

Genesys•Raleigh, NC

1d•$161,500 - $283,900•Remote

About The Position

This role shapes the future of financial data at scale by transforming how critical business data is modeled, governed, and delivered across the organization. You will lead the evolution of a modern data platform, migrating complex pipelines into AWS while ensuring auditability, performance, and trust for financial reporting. At Genesys, we are redefining how organizations engage with customers through AI-driven experiences, and this role directly supports that mission by enabling accurate, timely, and reliable data for strategic decision-making. You will operate with high autonomy, influencing architecture, engineering standards, and cross-functional data strategy across Finance and Customer Success. This position offers visibility into enterprise initiatives and the opportunity to drive platform-level impact while expanding technical and leadership capabilities. This position is not eligible for employer-sponsored work authorization (e.g., H-1B, TN, O-1, or other employment-based visas), now or in the future. Applicants must be legally authorized to work in the United States at the time of application and throughout employment without the need for current or future employer sponsorship.

Requirements

Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical field, or equivalent practical experience
6+ years of experience building production-grade data platforms or modern data warehouse solutions
Expert-level SQL skills, including complex query design, performance tuning, and large-scale data modeling
Strong Python development experience for building robust data pipelines and automation
Proven experience working with cloud-based data platforms, including Snowflake and AWS services
Demonstrated expertise in CI/CD pipelines, Git-based workflows, and automated testing frameworks
Strong understanding of data governance, observability, and monitoring best practices
Ability to communicate complex technical concepts effectively to both technical and business stakeholders
Familiarity with AWS services such as Glue, S3, and CloudWatch for data pipeline orchestration

Nice To Haves

Experience designing and implementing financial data models in regulated environments
Experience with data lineage, cataloging tools, and enterprise data governance frameworks
Track record of leading cross-functional data initiatives with measurable business impact

Responsibilities

Own the end-to-end migration of data pipelines from Snowflake to AWS, improving scalability, cost efficiency, and system observability
Design and implement dimensional data models that enable accurate, SOX-compliant financial reporting and analytics
Build and evolve Medallion Architecture data layers, ensuring high-quality, testable Silver and Gold datasets
Drive performance optimization across SQL transformations and data processing workflows to reduce cost and improve execution efficiency
Establish and enforce engineering standards for testing, deployment, and documentation across data platforms
Implement data quality frameworks that improve data reliability through validation, anomaly detection, and monitoring
Lead architecture decisions and influence technical direction across Strategic Finance and Customer Success data ecosystems
Partner with business stakeholders to translate complex requirements into scalable, production-ready data solutions