Data Architect

Summary

Join Abnormal Security as a Data Architect to design and implement scalable, secure, and intelligent data systems. You will define the architecture and strategy for the enterprise data ecosystem, focusing on governance, quality, and usability. This foundational role supports cross-functional needs, enabling trusted data for analytics, AI, and business automation. You will implement data governance frameworks, manage enterprise data models, and guide the evolution of the cloud-native data infrastructure. The ideal candidate possesses deep technical expertise, strong business acumen, and a passion for building scalable systems. You will collaborate with cross-functional teams and mentor engineers and analysts.

Requirements

• 7+ years of experience in data architecture, data engineering, or related roles in modern data environments
• Expertise in cloud-based data warehousing (especially Snowflake), SQL, and data modeling techniques
• Proven experience implementing enterprise data governance and MDM programs
• Familiarity with data orchestration and transformation tools like dbt or Airflow
• Strong understanding of metadata, lineage, and data quality frameworks
• Deep knowledge of data security, compliance, and privacy in distributed environments
• Demonstrated ability to work cross-functionally and translate business needs into technical architecture
• Excellent written and verbal communication skills, with a bias for documentation and clarity
• Experience leading data initiatives in cybersecurity or fast-growing startup settings

Responsibilities

• Design and implement scalable, secure, and governed data architecture across enterprise systems
• Establish and maintain enterprise data models, taxonomies, and metadata management standards
• Lead the rollout of master data management (MDM) and data governance frameworks
• Architect and optimize our Snowflake data warehouse and associated tools (e.g., dbt, Fivetran, Sigma)
• Define data integration patterns and ensure high data quality, consistency, and lineage
• Collaborate across IT, GRC, GTM, and Product teams to support cross-functional data needs
• Enable self-service analytics and AI/ML capabilities by structuring data for usability and accessibility
• Monitor, document, and continuously improve data flows, storage, access, and compliance
• Evaluate and integrate cloud-native data technologies, staying current with trends in data and AI
• Mentor engineers and analysts on data modeling, system design, and governance best practices

Preferred Qualifications

• Exposure to AI/ML systems and a working knowledge of data readiness for AI applications
• Experience integrating BI tools (e.g., Sigma, Looker, Tableau) with governed data models
• Familiarity with data catalogs, lineage tools, or data mesh principles
• Previous work with real-time or event-based data architectures
• Certifications in Snowflake, cloud platforms (AWS, GCP, Azure), or data governance frameworks

Benefits

• Bonus
• Restricted stock units (RSUs)
• Benefits