About the role

Who We Are Ontic provides software that helps corporate and government security teams identify threats, assess risk, and respond faster to keep people and organizations safe. Its AI-powered Connected Intelligence Platform unifies security operations and data into a centralized system of record, enabling organizations to conduct risk assessments, protect against workplace violence, and manage threats and incidents more efficiently. Fortune 500 companies and federal agencies rely on Ontic to support security programs such as executive protection, threat intelligence, and corporate investigations. Learn more at ontic.ai http://ontic.ai or follow us on LinkedIn https://www.linkedin.com/company/ontic-technologies/. Who You Are We are hiring a dedicated R&D Analytics Engineer to help build and scale the data and AI foundation of our enterprise SaaS business. Reporting to the Sr. Director of AI & Analytics within our centralized Operations organization, this is a highly hands-on role focused on architecting scalable analytics systems and AI-enabled workflows that power decision-making across the company. You will design the core data models, architecture, and reusable assets that serve Product, Engineering & Design — while helping redefine what an analytics function looks like in the age of AI. This is a foundational hire with high ownership and long-term growth potential. What You'll Do 1. Enterprise Data Modeling & Architecture - Design and maintain scalable dbt data models in Snowflake that serve as trusted sources of truth across the business - Architect data pipelines and transformation workflows using Fivetran and modern ELT practices - Develop durable, extensible data assets that evolve as the company scales - Establish modeling standards, documentation practices, and governance frameworks - Partner with RevOps and Finance to define and operationalize core SaaS metrics (ARR, retention, expansion, pipeline, etc.) 2. AI-Enabled Systems & Workflow Integration - Build data foundations that power internal AI applications and LLM-enabled workflows - Prototype and productionize AI-driven operational use cases - Integrate analytics and AI into everyday workflows using tools such as Notion, Cursor, Glean, and other emerging platforms - Design systems that embed data directly into operational processes — not just dashboards 3. Cross-Functional Analytics Infrastructure - Partner with leaders across Sales, CS, Marketing, Finance, Product, and Engineering to translate business needs into scalable technical systems - Create reusable data assets that enable activation via Hightouch and analysis via Omni - Ensure architecture is scalable, secure, and adaptable to evolving enterprise requirements Our Stack Analytics: Fivetran, dbt, Snowflake, Hightouch, Omni AI & Knowledge Systems: Notion, Cursor, Glean Experience with these tools is helpful but not required. Strong fundamentals and the ability to quickly learn new technologies matter more than prior tool exposure. What We’re Looking For - 3-6 years of experience in analytics engineering, data engineering, or similar hands-on roles - Strong SQL skills and deep understanding of modern data modeling (dimensional modeling, transformations, data contracts, etc.) - Experience building in cloud data warehouses (Snowflake, BigQuery, Redshift, etc.) - Comfort working in a fast-moving, evolving AI tooling landscape - Systems-level thinker who designs for scalability, extensibility, and flexibility - Naturally curious and energized by solving ambiguous problems - Pride in building clean, durable architecture — not just shipping quick fixes - Strong communication skills and ability to collaborate across business and technical teams - Nice to have: Experience with Pendo, Amplitude, Heap, or Mixpanel Why This Role Matters We are not building a traditional BI function. We are building an AI-augmented analytics capability that: - Emb