Data Engineer

About Us

Act Security is an action-first cloud security platform built for the AI era.

For years, organizations have piled up access they never use. That debt was survivable when attacks moved at human speed. It isn't anymore. AI now finds and exploits access paths faster than any team can triage them, and AI agents are operating inside production systems with real autonomy to act. Access has become the attack surface, and chasing findings one at a time is a losing game.

Act systematically shrinks the access surface across your cloud, enforcing deterministic boundaries on what people, workloads, and AI agents can reach. We reason across identity, network, and AI access together- the three control planes that decide what anything can touch- and we enforce through the cloud-native controls you already own. No agents, nothing new to deploy, nothing taken offline. The result is a cloud that's structurally harder to attack and a security posture that holds between audits instead of quietly eroding.

We're early-stage, well-funded, and moving fast - built by repeat security operators who previously created Medigate (acquired by Claroty). If you want to build something that matters from the ground up and ship to production within days, this is the place.

Our Culture

We live by three values: Win, Learn, Have Fun. We play to win- we set ambitious goals and hold ourselves to high standards. We learn constantly- from customers, from each other, and from our mistakes. And we have fun doing it: we believe great work happens when people enjoy working together.

The Role

We are looking for a Data Engineer to join our team and take ownership of the data infrastructure that powers our cloud security platform. This role offers the opportunity to work on cutting-edge technology and make a significant impact in the field of cybersecurity.

What Will You Do

• Build and maintain ETL/ELT pipelines that ingest data from cloud provider APIs (AWS, Azure, GCP) and normalize it into a consistent internal data model
• Design data models purpose-built for specific product features — clean, aggregated, and ready for fast consumption
• Own data completeness: backfills, historical data loading, incremental load patterns, and enrichment layers
• Ensure data quality through completeness checks, anomaly detection, and proactive alerting
• Design and optimize the storage and query layer — partitioning, query performance, and cost efficiency at scale
• Work closely with backend engineers and Product to reduce ad-hoc data dependencies and accelerate feature development
• Leverage AI tools as part of your daily workflow — we build with AI, not just for AI
• Improve our data infrastructure, tooling, and practices as we grow
  
  

• 3+ years of hands-on Data Engineering experience - pipelines, models, and data infrastructure in production
• Strong SQL skills
• Experience with cloud data warehouses (Redshift, BigQuery, Snowflake, or similar) and datalake architecture (S3/Trino)
• Solid understanding of data modeling: normalization, dimensional modeling, aggregations, and incremental patterns
• Experience working with cloud provider APIs or ingesting data from external systems at scale
• Strong sense of ownership, clear communication, and a genuine service orientation - you follow through and people trust you
• Comfortable in a startup environment where the scope is broad and the playbook is still being written
• Experience with orchestration tools (Temporal, Airflow, Prefect, or similar) and/or dbt- an advantage
  
  

• Real ownership- this is an early-stage company where engineers drive decisions
• AI-native environment- you'll join an AI-native team. We help customers secure their AI workloads, build intelligent automation into our product, and use AI tools every day as part of how we build and ship.
• Top-tier team- founders with deep security and product experience, surrounded by a team of experts and backed by leading investors
• Competitive package- strong salary, meaningful equity, and the upside of joining early