Data Platform Engineer I — Build Scalable Systems

Abnormalsecurity; United States; On-site; USD 122,400 - 176,000; Full time

Job summary

Abnormal AI is hiring a Software Engineer I for its Data Platform team. You’ll design, build, and operate core components of our cloud data infrastructure, working with engineers and data scientists to scale data-heavy workloads.

The role emphasizes ownership, learning, and collaboration, with opportunities to contribute to tools and services that simplify data-system adoption across teams. Prior experience and strong fundamentals are valued.

Qualifications

• 1+ years of professional software engineering experience (backend, distributed systems, or infrastructure).
• Solid programming skills in Python, Go, or similar languages.
• Strong fundamentals: data structures, clean code, testing, debugging.
• Interest in AWS, Databricks, and technologies in our stack (databases, streaming, orchestration).
• Curiosity, problem-solving, and good communication; ability to work independently or in a team.

Responsibilities

• Contribute to design, development, and operation of core components of Abnormal’s data platform.
• Build tools/services to help other teams adopt and scale data systems.
• Automate infrastructure and operations to improve reliability, performance, and scalability.
• Apply GenAI techniques to enhance developer/operator experiences.
• Collaborate across teams to solve scalability and reliability challenges.
• Own projects and deliver features end-to-end with guidance from senior engineers.

Skills

1+ years software engineering

Python

Go

Data structures

Testing

Debugging

AWS Databricks stack

Communication

Education

Bachelor's degree in CS or related field

Tools

PostgreSQL

OpenSearch/Elasticsearch

Redis

RocksDB

DynamoDB

Job description

Abnormal AI is hiring a Software Engineer I for its Data Platform team. You’ll design, build, and operate core components of our cloud data infrastructure, working with engineers and data scientists to scale data-heavy workloads.

The role emphasizes ownership, learning, and collaboration, with opportunities to contribute to tools and services that simplify data-system adoption across teams. Prior experience and strong fundamentals are valued.