Senior Developer, Data Engineering

This is a remote position.

• 5+ years of experience building enterprise data solutions on Microsoft Azure, including hands-on production experience with Microsoft Fabric.
  
• 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.
  
• General .NET/C# experience, including Azure Function Apps for serverless, event-driven data workflows.
  
• Experience building data pipelines, lakehouses, 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 warehouses/lakehouses that support scalable reporting and analytics.
  
• Strong communication skills and ability to work in a collaborative, agile team environment.
  

• Good to strong understanding of GraphQL APIs for data integration.
  
• Experience with Azure Data Factory, Databricks, or Azure Synapse.
  
• Hands-on experience with CI/CD pipelines using Azure DevOps or GitHub.
  
• Familiarity with C#, .NET, or React beyond core Function App development.
  
• Bachelor's or master's degree in computer science or a related field is preferred.
  
• Familiarity with AI/ML integration in SaaS applications.
  
  

• Design, build, and maintain enterprise data solutions on Microsoft Fabric, including lakehouses, 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.