Senior Data Engineer

Company Overview: About Us: Atlanta-based Incident IQ is the leading workflow management platform built exclusively for K-12 districts. Trusted by over 2,000 districts, Incident IQ powers mission-critical services for more than 12 million students and educators nationwide. By connecting technology and operational workflows, Incident IQ enables schools to streamline processes, reduce administrative burdens, and focus on what matters most: supporting students. Purpose: Incident IQ is committed to creating a future where every K-12 district operates with seamless efficiency. When operations are unified on a single platform, districts gain the clarity and control needed to build a stronger foundation for student success. We’re focused on delivering the tools, support, and partnerships that help make that vision a reality. Mission: Incident IQ is on a mission to eliminate the friction of disconnected systems and clunky workflows that slow schools down. We’re reimagining the critical work that happens behind the scenes, bringing visibility, efficiency, and impact to the processes that keep classrooms running. By streamlining the complex, automating the routine, and surfacing the insights that matter most, we can create the conditions for educators to teach, students to thrive, and districts to shape the future of education. Senior Data Engineer Overview: We are seeking an experi [... source excerpt omitted ...] ta Engineer to lead the design, architecture, and population of our new BI data warehouse. This role is highly cross-functional and critical to Incident IQ's next phase of growth. You will be responsible for aggregating complex data streams from our core SaaS platform and third-party systems into a centralized data warehouse/lake. You will own the analytics foundation end-to-end, serving as an architect-engineer. This is a genuine greenfield seat: the analytics foundation you build becomes how the company and its customers answer their most important questions. Key Responsibilities Data Warehouse Architecture: Design, implement, and scale a modern BI data warehouse/data lake fr [... source excerpt omitted ...] ironment stood up early and built out over time, rather than a spreadsheet-first interim. You will design at a grain that serves internal analytics today and groundwork for future customer-facing analytics. Data Pipeline Engineering: Build and maintain robust, automated ETL/ELT pipelines to extract and aggregate data from diverse sources, beginning with our Azure-hosted product platform and extending to operational systems (e.g., CRM) and other external APIs as product usage pipelines stabilize. Platform Evaluation and Recommendation: Own the written platform recommendation scored on refresh latency, aggregation performance at full volume, schema evolution, tenant isolation, th