Summary 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