R&D Analytics Engineer

Summary

Ontic provides software that helps corporate and government security teams identify threats, assess risk, and respond faster through an AI-powered Connected Intelligence Platform. The R&D Analytics Engineer will architect scalable data models, analytics systems, and AI-enabled workflows, while partnering cross-functionally to build reusable infrastructure that supports enterprise decision-making.

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

Skills

• 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

Qualifications

Must Haves

• 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

Benefits

• Medical, Vision & Dental Benefits
• 401k
• Stock Options
• HSA Contribution
• Learning Stipend
• Flexible PTO Policy
• Quarterly company ME (mental escape) days
• Generous Parental Leave policy
• Home Office Stipend
• Mobile Phone Reimbursement
• Home Internet Reimbursement for Remote Employees
• Anniversary & Milestone Celebrations