United States onlySummary of roleAs 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
