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 of experience as a Data Engineer
- 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
- Excellent communicator who thrives working across cross-functional teams
- Experience working alongside AI agent systems and evaluating their outputs
Nice to Have:
- 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).
As an equal-opportunity employer, we are committed to a team defined and empowered by diversity. We consider qualified applicants without regard to race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We are waiting for you!
We build AI for a living, and we encourage candidates to use it to prep, research, and sharpen their best work. But we're hiring humans, not chatbots. We want the real you. Use AI to tighten your resume, prep for interviews, research Torq, and outline ideas for written responses. Show up as yourself for live interviews, final assessments (the voice, logic, and reasoning need to be yours), and anywhere we're evaluating how you think — not how you prompt.
Excited about our vision and ready to make an impact as we grow? We'd love to see what you can bring to the team.
Skills Required
- 4+ years as a Data Engineer or similar data-focused engineering role.
- Strong proficiency in SQL and Python.
- Experience building and owning scalable data pipelines and transforming raw data into normalized models (production-ready).
- Experience with relational data modeling and integrating data from external APIs.
- Analytical and product mindset; ability to profile datasets, validate findings, and translate insights into scalable solutions.
- Ownership and strong communication/collaboration across cross-functional teams.
- Experience working alongside AI agent systems and evaluating their outputs.
- Background in cybersecurity (security operations, identity, endpoint, alert data).
- Experience with 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).
What We Do
Torq's no-code automation modernizes how security & operations teams work with easy workflow building, limitless integrations and numerous pre-built templates.
.png){kind=logo}
