Abnormal Security
Staff Software Engineer, Data Platform
Abnormal Security, Myrtle Point, Oregon, United States, 97458
Overview
Enterprises of all sizes trust Abnormal Securitys cloud products to stop cybercrimeand those products depend on data: reliable, scalable, and secure access to it. The Data Platform team builds and operates the core storage, streaming, and processing systems that power Abnormals AI-driven detection and prevention. Our mission is to provide robust, self-service data platforms that enable engineering and data science teams to innovate quickly, confidently, and at scale. Were looking for a
Staff Software Engineer
to drive the next generation of Abnormals data platform. In this role, youll set technical direction, lead ambitious cross-team initiatives, and mentor engineers while shaping how data flows and scales across our systems. Staff Engineers are expected to be technical leaders at Abnormal. The ideal candidate: Tackles complex, ambiguous problems and turns them into actionable plans. Leads by example and dives deep when needed. Embodies our VOICE values and builds platforms as product offerings that delight users. Earns trust with our stakeholders across Engineering, Data Science, Analytics and Product through thoughtful collaboration. What you will do
Define and drive the architecture and roadmap for Abnormals 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 Abnormals AI-native data workflows: data pipelines, feature storage, offline/online consistency, model evaluation, and data governance. Must Haves
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. Nice to Haves
Experience with multi-tenant, multi-region or regulated platforms, including isolation, data governance, and guardrails. Prior leadership of cross-org migrations (e.g., to event-driven architectures or unified data platforms). How We Work
Product mindset: we treat our data platform as a product with clear APIs, docs, SLAs, and adoption metrics. Automation first: paved paths and golden configs over bespoke solutions. Measured outcomes: reliability, latency, cost, and developer experience drive our success. #LI-ML1 At Abnormal AI, certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. Base salary range: $209,800 $246,800 USD Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please see the policy. If you would like more information on your EEO rights under the law, please see the rights. #J-18808-Ljbffr
Enterprises of all sizes trust Abnormal Securitys cloud products to stop cybercrimeand those products depend on data: reliable, scalable, and secure access to it. The Data Platform team builds and operates the core storage, streaming, and processing systems that power Abnormals AI-driven detection and prevention. Our mission is to provide robust, self-service data platforms that enable engineering and data science teams to innovate quickly, confidently, and at scale. Were looking for a
Staff Software Engineer
to drive the next generation of Abnormals data platform. In this role, youll set technical direction, lead ambitious cross-team initiatives, and mentor engineers while shaping how data flows and scales across our systems. Staff Engineers are expected to be technical leaders at Abnormal. The ideal candidate: Tackles complex, ambiguous problems and turns them into actionable plans. Leads by example and dives deep when needed. Embodies our VOICE values and builds platforms as product offerings that delight users. Earns trust with our stakeholders across Engineering, Data Science, Analytics and Product through thoughtful collaboration. What you will do
Define and drive the architecture and roadmap for Abnormals 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 Abnormals AI-native data workflows: data pipelines, feature storage, offline/online consistency, model evaluation, and data governance. Must Haves
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. Nice to Haves
Experience with multi-tenant, multi-region or regulated platforms, including isolation, data governance, and guardrails. Prior leadership of cross-org migrations (e.g., to event-driven architectures or unified data platforms). How We Work
Product mindset: we treat our data platform as a product with clear APIs, docs, SLAs, and adoption metrics. Automation first: paved paths and golden configs over bespoke solutions. Measured outcomes: reliability, latency, cost, and developer experience drive our success. #LI-ML1 At Abnormal AI, certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. Base salary range: $209,800 $246,800 USD Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please see the policy. If you would like more information on your EEO rights under the law, please see the rights. #J-18808-Ljbffr