Software Development Engineer

Key Responsibilities

• Engineering & Development: Design and implement scalable solutions within Gainsight NXT and CRM platforms (Salesforce/Dynamics), including configuration of rules, workflows, dashboards, and data models.
• Integration Development: Build and maintain integrations across Microsoft Dynamics, Azure, Databricks, SnapLogic, and middleware platforms to ensure seamless data flow and automation.
• Data Engineering: Develop data models, pipelines, and transformations that support customer health scoring, lifecycle management, and predictive analytics.
• AI Enablement: Collaborate with architects and product managers to prototype and deploy AI-driven features such as sentiment analysis, escalation triggers, and predictive insights.
• System Reliability: Ensure solutions are secure, reliable, and performant, following enterprise standards for data governance, testing, and monitoring.
• Collaboration: Partner with Business Systems Analysts, Product Owners, and Scrum Teams to translate requirements into technical deliverables.
• Continuous Improvement: Research and adopt new technologies, frameworks, and practices that improve development efficiency and system scalability.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
• 5+ years of professional software development experience in enterprise or SaaS environments.
• Strong skills in SQL, Python, Java, or C# for backend/data engineering.
• Experience with Gainsight NXT configuration is highly desirable; alternatively, Salesforce or Microsoft Dynamics configuration experience is strongly valued.
• Experience developing integrations with CRM platforms and middleware/iPaaS (SnapLogic or equivalent).
• Proficiency with cloud platforms (Microsoft Azure preferred) and distributed data systems (Databricks, Spark).
• Experience with frontend/UI frameworks (JavaScript, React, Angular, or equivalent) and building data-driven dashboards.
• Familiarity with REST APIs, event-driven architectures, and microservices.
• Strong problem-solving, debugging, and performance optimization skills.
• Interest or experience in AI/ML solutions for enterprise workflows.