Platform Engieer

TEKsystems•San Jose, CA

3d•$70 - $80•Hybrid

About The Position

We are seeking a highly skilled Software Development Engineer to design, develop, and scale solutions within our Customer Success Management (CSM) ecosystem. This role is focused on building integrations, data pipelines, and platform extensions across Gainsight NXT and our enterprise technology stack. The ideal candidate will combine strong engineering expertise with a deep understanding of data models, APIs, and enterprise platforms, while contributing to the adoption of AI-driven solutions in the Customer Success space.

Requirements

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 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.

Nice To Haves

Gainsight NXT configuration is highly desirable; alternatively, Salesforce or Microsoft Dynamics configuration experience is strongly valued.

Responsibilities

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