Abnormal Security is seeking a Data Architect to lead the design and execution of scalable, secure, and intelligent data systems that power our business operations and decision-making. As part of the IT organization, you will define the architecture and strategy for our enterprise data ecosystem, with a focus on governance, quality, and usability. Your work will support cross-functional needs—including G&A, GTM, and product—enabling trusted data for analytics, AI, and business automation.

This is a foundational role for Abnormal’s data future. You’ll be responsible for implementing data governance frameworks, managing enterprise data models, and guiding the evolution of our cloud-native data infrastructure. The ideal candidate brings deep technical expertise, strong business acumen, and a passion for building systems that scale with excellence

Who you are

A systems thinker who designs data architecture to be modular, scalable, and business-aligned.
Obsessed with data quality and integrity—recognizing governance and MDM as enablers of speed and trust.
Hands-on technical leader with experience in enterprise data platforms like Snowflake, dbt, and modern ETL tools.
Someone who thrives in fast-paced environments with shifting priorities and complex stakeholder needs.
Able to translate business needs into technical solutions while balancing flexibility, security, and compliance.
An evangelist for data standards, best practices, and the long-term value of clean architecture.
Naturally collaborative, empathetic, and driven by a desire to support teams through better data.
Familiar with the demands of cybersecurity or high-growth startup environments.
Committed to velocity, ownership, and continuous improvement as core ways of working.
Passionate about the potential of AI and machine learning, and how clean data accelerates that future.

What you will do

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.

Must Haves

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.

Nice to Have

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.

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