About the job
Transforming Education Through Technology
At Kognity, we believe that education has the power to change lives. Yet, technology has not yet fulfilled its promise to enhance learning experiences. We're on a mission to change that.
As a dynamic EdTech scale-up of 125 passionate professionals, we empower educational institutions in over 120 countries. Our innovative platform fuses advanced pedagogy with artificial intelligence, enabling both students and teachers to excel, from international schools to high schools across the United States.
Why Join Kognity?
Innovative Education Solutions – Spearhead the evolution of AI-driven learning tools.
Global Impact – Our technology is utilized in educational settings worldwide, impacting over 120 countries.
Collaborative Environment – Become part of an intelligent, ambitious team that prioritizes meaningful contributions over ego.
High-Performing Teams – Collaborate with talented colleagues across product development, engineering, and AI, all committed to raising industry standards.
Your Role
You will lead the analytics engineering efforts, transforming raw data into well-structured, reliable metrics and scalable, business-ready data products that facilitate informed decision-making throughout the organization.
Joining a small, focused team equipped with a solid data foundation, modern tools, and a clear strategic direction, you will be instrumental in developing a self-service data platform and advancing our metrics-driven approach. This position offers significant ownership, a flat organizational structure, and access to cutting-edge technologies, providing a unique opportunity to influence the future of analytics at a rapidly growing company.
Your Responsibilities:
Design, implement, and sustain scalable data models and transformations to produce clean, trustworthy datasets ready for business use.
Collaborate with fellow analytics engineers to integrate new data sources, automate workflows, and ensure high-performance data pipelines.
Develop and maintain a semantic layer to standardize key metrics and definitions throughout the organization.
Establish data quality checks, testing frameworks, and governance practices to ensure data accuracy and consistency.
Work alongside stakeholders in product, finance, and sales teams to convert business requirements into effective analytical and modeling solutions.
Continuously enhance tools, processes, and architecture by adopting modern analytics engineering best practices and exploring AI innovations.
