Senior Data Engineer, Finance

Be the one building AI-powered experiences where they matter most.   At Genesys, we help organizations create better customer experiences through AI-powered experience orchestration. Our platform connects people, systems, data and AI to help organizations deliver more personalized service, improve operational efficiency and build stronger customer relationships.   Help build, support and operate technology used by more than 8,000 organizations in over 100 countries – moving AI from possibility to production in real-world enterprise environments every day. *Note this role is remote US in EST or CST Role Overview: 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.

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 Required Qualifications: 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 Preferred Qualifications: 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