Senior Developer, Data Engineering

About the Organization Evention is redefining financial trust after checkout. Hospitality, retail, and entertainment businesses run on complex ecosystems of payments, payroll, tips, OTAs, and financial systems. But checkout is not the end of a transaction. It is the moment payment is authorized, not the moment financial accuracy is proven. As transactions move across systems, small errors can quickly turn into margin leakage, compliance risk, operational friction, and brand impact.

Evention exists to close that gap. As the financial trust layer for complex, high-volume operators, Evention helps organizations continuously validate financial activity after checkout to ensure what was paid, processed, and reported is accurate across systems, locations, and workflows. Our platform automates reconciliation, surfaces exceptions before they become larger problems, and helps finance and operations teams protect margins, improve compliance, and lead with confidence.

Since 2004, Evention has partnered with leading hospitality, retail, gaming, grocery, convenience, and entertainment brands to solve problems most businesses do not realize they have until they become costly. We are building a company that moves quickly, values curiosity, and challenges legacy ways of working. If you enjoy solving meaningful problems, working cross-functionally, and helping shape what comes next, you will fit right in.

We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status or any other characteristic protected by law.

The Senior Developer, Data Engineering will lead the design, development, and delivery of Evention's enterprise data platform, built primarily on Microsoft Fabric. You will set technical direction for the data platform team, architect scalable data pipelines and analytics solutions, and build .NET-based serverless components for the workflows where Fabric is more than the job calls for. You'll partner closely with product, engineering, and business stakeholders to turn data into a strategic asset for our customers.

• Lead and mentor the data platform team, setting technical direction across data engineering, analytics, and architecture initiatives.
• Design, build, and maintain enterprise data solutions on Microsoft Fabric, including lake houses, data pipelines, and ETL/ELT frameworks.
• Architect scalable data models and analytics solutions that support reporting, BI, and downstream product needs across Evention's platform.
• Develop Spark notebooks and distributed data processing jobs for large-scale data transformation and integration.
• Build .NET-based Azure Function Apps and serverless, event-driven workflows for processes where Fabric is more overhead than the job needs.
• Build and maintain integrations and API connections to client data sources (PMS, POS, OTA, and other systems) feeding the data platform.
• Partner with product managers, engineering leads, and business stakeholders to translate requirements into technical and architectural solutions.
• Establish and enforce best practices for data pipeline development, CI/CD, monitoring, data quality, and governance.
• Perform code and design reviews, mentor team members, and promote strong engineering and data practices.
• Stay current on Microsoft Fabric, Azure data services, and data engineering trends to guide platform strategy and continuous innovation.

Required

• 5+ years of experience building enterprise data solutions on Microsoft Azure, including hands-on production experience with Microsoft Fabric or Databricks.
• Proven experience leading, or acting as a technical lead for, a data engineering or data platform team.
• Strong Python skills for data engineering and pipeline development.
• Proficiency in PySpark, Pandas, or Polars libraries for Data Frame processing within Spark and Python notebook kernels.
• General .NET/C# experience, including Azure Function Apps for serverless, event-driven data workflows.
• Experience building data pipelines, lake houses, and ETL/ELT frameworks within Microsoft Fabric.
• Hands-on experience with Spark notebooks and distributed data processing.
• Strong SQL and T-SQL skills.
• Experience with spec-driven development and agentic AI-assisted development workflows.
• Strong data analytics and data architecture experience, including designing data models and…