We're looking for an experienced Senior BI Engineer to join our Data Team. In this role, you'll focus on building the data pipelines that power our cybersecurity data infrastructure. You'll own and evolve the foundational datasets that power our analysts, researchers, and security experts in detecting threats and investigating risks - and that feed the product features protecting our customers every day.
What you'll do
Build and maintain robust ETL/ELT pipelines that transform raw data into production-ready datasets used for threat detection, risk investigation, and customer-facing product features.
Design and develop scalable, maintainable data models in dbt (layered architecture, reusable components, documentation) supporting cybersecurity use cases such as detecting suspicious patterns, emerging risks, and behavioral anomalies across users and online platforms.
Take ownership of our cybersecurity data infrastructure (foundational datasets, governance, and observability) - maintaining, improving, and enriching it to support reliable, high-scale data delivery to detection and protection systems.
Orchestrate and monitor workflows with Airflow (scheduling, dependencies, retries, alerting, SLAs).
Partner with Security Analysts, Data Science, Research, and Product teams to understand their needs and translate them into reliable pipelines and datasets that power threat detection capabilities and customer protection.
Ensure data quality and reliability through testing, validation, and monitoring for critical security datasets.
What we're looking for
5+ years in BI Development / Analytics Engineering / DWH Development roles.
Expert SQL and strong experience with data modeling concepts (e.g., dimensional modeling, facts/dimensions, modular design).
Experience with ETL/ELT tools and modern data stacks (orchestration, transformations, CI/testing, monitoring).
Strong communication skills and a track record of delivering data solutions that power real product or operational outcomes.
Experience building data pipelines that feed production systems, detection engines, or operational data products.
Experience with cloud-based data technologies (GCP/AWS/Azure) and modern warehouses (BigQuery/Redshift/Snowflake).
Experience in Python is an advantage.
Familiarity with web technologies and protocols (HTTP, DNS, HTML, etc.) is an advantage.
Cybersecurity or security data experience is an advantage.
Hands-on experience with dbt and Airflow in production environments is an advantage.
Requirements
