Analytics Engineer

Ontic

16h•Remote

About The Position

Ontic provides software that helps corporate and government security teams identify threats, assess risk, and respond faster to keep people and organizations safe. Its 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. Ontic is hiring its first dedicated Analytics Engineer to help build and scale the data and AI foundation of its enterprise SaaS business. This role reports to the Sr. Director of AI & Analytics within the centralized Operations organization and is highly hands-on, focusing on architecting scalable analytics systems and AI-enabled workflows that power decision-making across the company. The Analytics Engineer will design core data models, architecture, and reusable assets for Sales, Customer Success, Marketing, Finance, Product, and Engineering, while helping redefine the analytics function in the age of AI. This is a foundational hire with high ownership and long-term growth potential.

Requirements

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 Haves

Experience with Fivetran
Experience with dbt
Experience with Snowflake
Experience with Hightouch
Experience with Omni
Experience with Notion
Experience with Cursor
Experience with Glean

Responsibilities

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.)
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
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