Our client tackles network security challenges from a different angle. They leverage complex datasets and machine learning to predict cyber attacks as an early warning system before they are launched. Based in sunny San Diego, CA, we recently closed a round of Series A funding and are seeking a Senior Software Engineer to join our engineering team.

The role will design, build, and maintain scalable data infrastructure that supports large-scale data processes including analytics, reporting, and machine learning initiatives. This role requires expertise in AWS Redshift, Aurora (MySQL), Python, ETL pipeline development, and ORM frameworks. If you have experience working with complex data schema design, high-volume transactional systems, and enjoy optimizing data workflows, we’d love to hear from you.

***This position is not open for remote work, but hybrid, which means you must be located in the San Diego area and requires a US citizenship.***

Key Responsibilities

• Architect, build, and maintain scalable data pipelines for structured and unstructured data across various sources.
• Design and optimize OLTP and OLAP data schemas for efficient storage, retrieval, and processing.
• Develop and manage ETL processes to transform and integrate data from Aurora/MySQL to and from AWS Redshift, and other sources.
• Implement best practices in data governance, performance optimization, and security across databases.
• Collaborate with data scientists and analysts to ensure data availability for machine learning and analytical workloads.
• Utilize Python and ORM frameworks for data modeling, transformation, and workflow automation.
• Monitor and improve database performance, identifying bottlenecks and implementing optimizations.
• Work with AWS services such as EC2, ECS, S3, Lambda, for scalable data processing.
• Ensure data quality, consistency, and compliance with regulatory standards (GDPR, CCPA, etc.).

Required Skills & Experience

• 5+ years of experience in data engineering, database architecture, or similar roles.
• Strong expertise in AWS Redshift, Aurora / MySQL, and other relational databases.
• Proficiency in Python (v3.8+) and experience with ORM frameworks.
• Experience designing and implementing ETL pipelines for large-scale transactional and analytical data.
• Familiarity with data modeling best practices for OLTP and OLAP workloads.
• Experience handling high-throughput OLTP processes with transactional integrity.
• Strong understanding of SQL query optimization and database indexing strategies.
• Excellent problem-solving and troubleshooting skills for debugging data inconsistencies and performance issues.

Preferred Qualifications

• Exposure to machine learning workflows and integrating ML models into data pipelines is a big plus.
• Hands-on experience with data warehousing best practices in AWS Redshift.
• Understanding of serverless architectures and cloud-native data solutions.
• Experience working with large-scale distributed systems.

Education & Work Authorization

• Bachelor’s degree in Computer Science, Engineering, Math, or Statistics (Preferred).
• Work authorization: United States (Required).

What We Offer

• Competitive salary, benefits, and equity options (if applicable).
• Work in a fast-paced, tech-driven environment with a strong engineering culture.
• Opportunity to work on cutting-edge data infrastructure with high scalability requirements.
• Career growth opportunities in data engineering and machine learning.
• Flexible work arrangements.