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.

What You Bring to the Table:

• 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.

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!