Remote
Software Architect - Data Platform
About this role
About Us Our leading SaaS-based Global Employment Platform™ enables clients to expand into over 180 countries quickly and efficiently, without the complexities of establishing local entities. At G-P, we’re dedicated to breaking down barriers to global business and creating opportunities for everyone, everywhere. Our diverse, remote-first teams are essential to our success. We empower our Dream Team members with flexibility and resources, fostering an environment where innovation thrives and every contribution is valued and celebrated.
The work you do here will positively impact lives around the world. We stand by our promise: Opportunity Made Possible. In addition to competitive compensation and benefits, we invite you to join us in expanding your skills and helping to reshape the future of work. At G-P, we assist organizations in building exceptional global teams in days, not months—streamlining the hiring, onboarding, and management process to unlock growth potential for all.
About The Position: As the Data Architect for the G-P Data Platform , you will be responsible for defining and driving the execution of our target-state, Databricks-native architecture across our data platform. This role balances strategic technical leadership with hands-on technical execution, ensuring our engineering investments align directly with customer expectations and our long-term technology vision. Reporting into the Architecture team , you will work in close partnership with Product Management, Cloud Operations, Business Operations, and cross-functional engineering squads.
You will act as a trusted technical advocate and mentor, driving platform consistency, lowering total cost of ownership (TCO), and further enhancing our world-class data analytics and reporting capabilities. What You Will Do: Target-State Architecture: Design and drive the execution of a scalable, cloud-native target-state architecture across the end-to-end software platform. Ingestion architecture: Define architectural patterns for scalable automated data ingestion Hands-on Execution & PoCs: Deliver hands-on proof-of-concepts (PoCs) alongside engineering teams using SQL, PySpark, Serverless Python or other platform languages to validate design decisions.