Analytics Platforms Architect

Join Tala as an Analytics Platforms Architect, where you'll be the senior technical leader responsible for making data easier to trust, understand, access, and use across the company. This hands-on role involves defining the architecture and technical direction for shared data and analytics platforms, building alongside engineers, and establishing how analytics teams and AI tools work with data. You'll work across multiple teams, drive technical initiatives, and raise the technical bar through mentorship and establishing standards.

• Define the technical architecture for Tala's semantic layer and shared analytics platform, establishing consistent, governed definitions for business metrics.
• Design and build production data models, pipelines, services, tooling, SDKs, and other platform components, taking ownership of specific platform capabilities.
• Lead technical initiatives that span Product, Engineering, Analytics, Finance, and Accounting, bringing clarity to ambiguous problems and driving technical decisions to completion.

• A track record of making complex architectural decisions and translating them into working systems
• Excellent communication skills and the ability to explain complex technical concepts to both technical and non-technical stakeholders
• Experience establishing trusted, governed, or standardized business metrics is highly valuable
• Experience with AI/LLM-powered analytics, data workflows, or agents is a strong plus
• Experience leading technical initiatives across multiple teams without necessarily having direct authority over those teams
• The ability and willingness to write production code and build alongside engineers
• Significant experience in data engineering, software engineering, analytics engineering, data platforms, or a related technical field
• Strong problem-solving skills and the ability to bring ambiguous or stalled initiatives to completion
• Experience working with financial, regulated, or highly sensitive data is a plus
• Experience designing and building large-scale or shared data platforms and infrastructure
• Strong experience with data architecture, data modeling, pipelines, and production systems