Data Engineer

Skeletons, lasers, tattoo buses — the Torq brand grabs attention like nothing else in cybersecurity. And we're growing like crazy, backed by Series D funding, 200% employee growth, and 300% revenue growth. Fueling Torq's momentum is our game-changing AI SOC platform, backed by a team and culture that makes Torq one of Forbes' Best Startup Employers in America, and a Business Insider 'startup to bet your career on'.

Life at Torq is all gas, no brakes. We're a team of relentless, collaborative go-getters pushing the boundaries of what's possible for security automation. Every role is an essential driver of Torq's success as the AI-native autonomous SecOps platform of choice for security teams across the Fortune 500.

We are looking for a strong Data Engineer to be part of one of Torq's most strategic initiatives - building the context graph that powers our AI-SOC platform. Our team is building the context layer behind Torq's AI Agents, transforming raw customer data into meaningful, normalized context that enables smarter autonomous security decisions.

This is a unique opportunity to join a brand-new, small, senior team with high ownership, strong product influence, and the chance to build foundational AI infrastructure from the ground up.

What You’ll Be Doing

• Think like a product person - collaborate with stakeholders and consumers to design meaningful data models and continuously validate them against real customer data.
• Run POCs work end to end - connect a new data source, ingest and normalize it, correlate entities across systems, and demonstrate the value.
• Do the analysis that shapes the model - profile new data, measure coverage and accuracy, and find the gaps that matter to the product.
• Integrate identity, endpoint, and security data sources - learn how each system exposes its data and turn it into reliable, consistent models.
• Build and own scalable data pipelines, transforming raw data into clean, normalized, and well-tested models using Python, SQL, and dbt.
  
  

• Analytical & product mindset: Able to investigate datasets, validate findings, and translate insights into scalable solutions.
• 4+ years as a Data Engineer or in a similar data-focused engineering role.
• Strong data engineering skills: Strong proficiency in SQL and Python, with experience in relational data modeling and integrating data from external APIs.
• Ownership: Independent and proactive, able to drive projects from raw data to production-ready solutions.
• Communication & collaboration: Excellent communicator who thrives working across cross-functional teams.
• Experience working alongside AI agent systems and evaluating their outputs.
  
  

• Background in cybersecurity, including security operations, identity, endpoint, and alert data.
• Experience with modern data stack tooling, including orchestration frameworks such as Airflow, Dagster, or similar.
• Hands-on experience building and maintaining dbt models and tests in production pipelines.
• Experience modeling data using graph databases (Neo4j or similar).