Data Engineer

About the Role

We're looking for a Data Engineer with 5+ years of experience to scale Twine's data operations, analytics foundation, and product-facing data capabilities.

This role goes beyond coding pipelines and warehouses – it requires understanding how the business operates, how stakeholders make decisions, and how to turn messy operational reality into trusted, usable data services.

You'll work closely with Customer Success, Solutions, Support, Sales, Product, R&D, and analysts to make data accessible, reliable, and actionable – for both humans and agents.

What We're Looking For

• A strong sense of data quality, reliability, privacy, and security.
• 5+ years in data engineering, analytics engineering, or similar data infrastructure roles
• 5+ years with cloud data warehouses (Snowflake, BigQuery, Redshift, or Databricks)
• Strong SQL, data modeling, and ELT/ETL experience, including DBT, orchestration tools (Dagster, Airflow, Prefect, or similar) and observability tools
• Experience profiling and optimizing pipelines and queries for scalability and cost efficiency
• Strong understanding of how business teams consume data, with the ability to translate stakeholder needs into robust data models
• Experience building high quality data products in a startup or fast-growing environment, with strong ownership and pragmatism
• Basic AI fluency – comfortable with tools like Claude or Codex, and familiar with semantic layers, RAG, or AI-assisted workflows

Nice to Have

• Experience with cybersecurity, IAM, IGA, SaaS, or enterprise software
• Experience building customer-facing analytics or data-powered product features

Why Join Twine

At Twine, data powers how we build, sell, support, and improve AI Digital Employees for cybersecurity teams. This is a high-impact role for someone who wants to shape the data operating system of a fast-growing AI security company – working alongside world-class engineers, researchers, and product builders to lay the data foundation for AI employees that execute real operational work end-to-end.