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