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Job description

Summary of role
As a Data/Solution Architect, you will design and build the intelligence backbone of MoonTech. You will architect a modern, scalable data platform that powers advanced analytics, AI use cases, marketing intelligence, and product decision-making.



This is a hands-on technical leadership role — ideal for someone who enjoys building systems from the ground up, writing production-grade code, defining architectural standards, and shaping the future of a data function. You will serve as the foundational data hire, setting the standards, infrastructure, and vision that will scale with the company.



Requirements & Qualifications



  • Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related technical field.



  • 8–10 years of experience in Data Engineering or Data Architecture.



  • Strong hands-on coding expertise in SQL and Python.



  • Experience building modern cloud data platforms (Google Cloud preferred).



  • Advanced experience with DBT and data modeling best practices.



  • Experience designing and implementing batch and streaming data pipelines.



  • Strong knowledge of data orchestration tools and workflow management.



  • Deep understanding of performance optimization, scalability, and system reliability.



  • Experience supporting analytics and AI use cases (forecasting, attribution, ML workflows).



  • Familiarity with data governance, data quality frameworks, and scalable architecture standards.



  • Experience in marketing, media, or performance-driven data environments is highly preferred.



  • Strong communication skills with the ability to translate complex architecture into business language.



Responsibilities



  • Design and implement a scalable, modern cloud-based data platform.



  • Architect and maintain batch and streaming data pipelines.



  • Define and enforce data modeling standards and governance practices.



  • Ensure platform performance, scalability, reliability, and security.



  • Lead technical design decisions and define long-term architectural roadmaps.



  • Review code, enforce engineering best practices, and guide future data hires.



  • Design data foundations to support forecasting, attribution modeling, CDP integrations, and marketing analytics.



  • Collaborate with Product, BI, and Data Science teams to create analytics-ready datasets.



  • Act as the internal technical authority for all data architecture decisions.



Key Skills:



Data Architecture • Cloud Data Platforms • DBT • Advanced SQL • Python • Streaming Pipelines • Data Modeling • AI Enablement • Performance Optimization • Scalability • Technical Leadership • Stakeholder Communication • Marketing Analytics





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