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Lead Data Engineer at Inception Point AI. Remote Location: Remote (United States Only). About Inception Point AI. Inception Point AI is a media-tech company building the next generation of AI-powered personalities, shows, and content brands. We blend cutting-edge AI tools with storytelling, design, and production discipline to create scalable, high-quality content across YouTube, social platforms, and podcasts. Our work sits at the intersection of creativity, automation, and entertainment — and we’re building systems that allow great ideas to move fast. . Role Overview. We are looking for a Lead Data Engineer who is not just an AI enthusiast, but a builder and visionary for our data ecosystem. Working on the frontier of AI and multi-agent orchestration, you will take ownership of our proprietary analytics system, transitioning it from a developer-led prototype into a production-grade engine. You will be the technical architect responsible for how we collect, store, and transform data to drive meaningful revenue, audience reach, and strategic licensing opportunities.. This is a "hybrid territory" role requiring a deep engineering core combined with a business analytics mindset. You will bridge the gap between complex data infrastructure and non-technical stakeholders, ensuring that our data is not just available, but accessible and actionable for everyone in the organization.. Core Responsibilities. System Ownership & Evolution:. Partner with the engineering team to lead the knowledge transfer of "Atlas" (built in Python), taking full architectural ownership and ensuring its continued health and progression.. Data Ingestion & Health:. Using Apache Airflow to manage and optimize the daily ingestion of analytics from multiple disparate sources (social media, podcast platforms, etc.) to ensure a clean, reliable, and "healthy" data stream.. Strategic Data Discovery:. Act as a "data detective" to identify what information we are missing and prioritize new data collection that aligns with our financial stability and growth levers.. Self-Service Enablement:. Build and maintain intuitive dashboards (e.g., Power BI or custom builds) that allow non-technical peers to answer basic everyday questions without needing manual engineering support.. Data Productization:. Transform raw data into structured, "customer-ready" packages to support our heavy push into data licensing.. Build vs. Buy Advisory:. Utilize your knowledge of the media analytics landscape to guide the organization on whether to build custom internal tools or leverage existing 3rd-party social media analytics solutions.. Required Skills & Qualifications. Technical Mastery:. Complete mastery of SQL and Airflow, along with a high proficiency with Python.. Cloud Infrastructure:. Deep familiarity with typical frameworks for cloud-based data storage and management.. High-Volume Experience:. Proven track record of working with very large datasets and high transaction volumes.. Analytical Rigor:. Ability to perform at least basic analysis on data, identifying issues, transforming datasets, and looking at information from multiple perspectives.. Communication:. Strong "people skills" with a genuine interest in interviewing stakeholders to understand the business questions they need the data to answer.. Success in the First 90 Days. 30 Days:. Complete deep-dive "Atlas" knowledge transfer with our Lead Engineer; interview key stakeholders/executives to understand their data "blind spots".. 60 Days:. Establish a prioritized roadmap for new data collection and ingestion health improvements.. 90 Days:. Deliver the first iteration of a self-service dashboard and initiate the first "customer-ready" data transformation for licensing.. Why This Role is Exciting. This is a rare opportunity to move beyond being a "cog in the machine" and instead become the founding architect of a data-driven media engine. .. You aren't just maintaining legacy systems; you are taking a high-potential prototype and building the "source of truth" for the entire company.. You will have the creative freedom to find the "hidden gems" in our data—uncovering audience behaviors that directly influence content creation and revenue. Your work will also directly transform from a back-end utility into a front-facing product, giving you the unique experience of building a commercialized data offering from the ground up in the fast-evolving creator economy.