About the job

About Us

We're reimagining how enterprise security teams operate in an AI-first world, transforming weeks of manual work into intelligent, automated workflows. Backed by tier-1 VCs, with second-time founders who've successfully built and sold cybersecurity companies, we're on a mission to empower security professionals to focus on strategic, high-impact work while AI handles the rest. If you're passionate about building the future of enterprise security, we want to hear from you.

About the Role

We are seeking a highly skilled Senior Data Engineer to design, build, and maintain scalable data pipelines and infrastructure for our platform. The ideal candidate will have extensive experience with ETL/ELT processes, analytical databases, and workflow orchestration. You will work on high-volume security data processing, building the data backbone that powers our AI-driven security platform. You will collaborate closely with Data Scientists, Security Researchers, and Full-stack Engineers.

Responsibilities

Design and build end-to-end data pipelines that ingest high-volume security data from multiple third-party sources, transform and normalize raw connector data into deduplicated schemas with memory-efficient stream processing, and orchestrate complex workflows across multi-tenant environments.
Write complex analytical SQL including aggregations, window functions, CTEs, and materialized views.
Manage database schemas across both an application data database and OLAP database, including migrations and cross-database federation.
Optimize stream processing pipelines to handle high-volume data ingestion with memory efficiency.
Apply best practices for data governance, security, and compliance including multi-tenant data isolation patterns, while continuously monitoring and optimizing pipeline performance for cost efficiency and reliability.

Requirements

5+ years of experience in data engineering or a similar role.
Strong proficiency in TypeScript/Node.js for building data pipeline code.
Expertise in OLAP databases such as Snowflake, BigQuery, Redshift, ClickHouse
Experience with relational databases schema design and migrations such as Aurora PostgreSQL
Hands-on experience with workflow orchestration tools (Temporal, Airflow, or similar):
Experience building ETL pipelines with streaming data transformations ( AWS Kinesis, AWS Kafka)
Strong experience with AWS cloud services
Proficiency in SQL for complex analytical queries.
Knowledge of data modeling, deduplication strategies, and distributed computing concepts. (Apache Spark, dbt, Apache Parquet)
Excellent problem-solving skills with the ability to troubleshoot complex pipeline issues.
Knowledge of event-driven architectures and multi-tenant data isolation patterns.
Experience with real-time data streaming and high-volume JSON processing. (Kafka Streams, AWS Kinesis Data Streams)

Nice to Haves

Experience in the cybersecurity domain.
Experience with ClickHouse.