Enterprises of all sizes trust Abnormal Security’s cloud products to stop cybercrime, and these products depend on reliable, scalable, and secure data access. The Data Platform team builds and operates the core systems that power Abnormal’s AI-driven detection and prevention. The role aims to drive the next generation of Abnormal’s data platform to enable engineering and data science teams to innovate quickly and at scale.
Requirements
- Proven experience building and scaling data-intensive, distributed systems in high-growth environments.
- 5+ years as a Senior+/Staff engineer building data platforms, infrastructure, or tools that materially increase engineering velocity and reliability.
- Depth in at least two of the following: Streaming systems (e.g., Kafka, Kinesis, SQS), Batch processing systems (e.g., Spark, Databricks, Airflow, DBT), Storage systems (e.g., PostgreSQL, MySQL, DynamoDB, RocksDB, Redis, OpenSearch, S3).
- Hands-on with our stack (or equivalent): Python, Golang, AWS, Databricks, Spark, Airflow, Kafka, Redis, RocksDB, PostgreSQL, Elasticsearch, Terraform, Kubernetes, etc.
- Strong fundamentals in distributed systems, observability, and reliability engineering (SLOs, incident management, capacity planning).
- A strong track record as a change agent, reshaping data platform strategy and delivering impactful, self-service offerings.
- Excellent ability and strong desire to onboard and mentor other engineers.
Responsibilities
- Define and drive the architecture and roadmap for Abnormal’s Data Platform, spanning storage, streaming, batch processing, and data infrastructure.
- Partner with engineers and data scientists to make pragmatic trade-offs, enabling a platform-first operating model and self-service data capabilities.
- Lead high-leverage technical initiatives such as scaling data systems across tenants and regions, improving resilience, and evolving our next-gen storage layer.
- Act as the technical lead for the team: shape quarterly plans, de-risk delivery, mentor engineers, and land impactful cross-org initiatives.
- Champion operational excellence across SLOs, availability, performance, incident response, and cost efficiency.
- Advocate for platform-as-a-product practices: crisp APIs, clear SLAs/SLOs, great docs, telemetry by default, and paved paths for developers.
- Guide Abnormal’s AI-native data workflows: data pipelines, feature storage, offline/online consistency, model evaluation, and data governance.
Other
- 5+ years as a Senior+/Staff engineer
- Proven experience building and scaling data-intensive, distributed systems in high-growth environments
- Excellent ability and strong desire to onboard and mentor other engineers
- Tackles complex, ambiguous problems and turns them into actionable plans
- Leads by example and dives deep when needed
