Data Architect

As a Data Architect at Abnormal Security, your primary responsibilities will include designing and implementing scalable and secure data architecture across enterprise systems, maintaining enterprise data models, and leading the rollout of data governance frameworks. You'll also optimize our Snowflake data warehouse, define data integration patterns, and support various cross-functional needs to enable efficient analytics and AI capabilities.

To qualify for the Data Architect position at Abnormal Security, you should possess at least 7 years of experience in data architecture or data engineering roles, with strong expertise in cloud-based data warehousing, particularly Snowflake. You’ll need a deep understanding of metadata frameworks, data security compliance, and the ability to translate business needs into effective technical architecture.

In the Data Architect role at Abnormal Security, you'll significantly contribute to data governance by implementing frameworks that ensure data quality and security. You'll establish and maintain data governance practices, oversee master data management initiatives, and promote best practices across teams to foster a culture of trust in data usage.

A successful Data Architect at Abnormal Security should be proficient in cloud data platforms like Snowflake, data transformation tools such as dbt, and systems for data orchestration. Familiarity with analytics tools, as well as an understanding of AI/ML as it relates to data systems, will also enhance your effectiveness in this role.

At Abnormal Security, the salary range for a Data Architect is competitive, ranging from $170,000 to $200,000 USD. This is accompanied by attractive benefits, bonuses, and a focus on equity, making our compensation package robust and tailored to the skills and experiences of the individual.

When discussing your experience with data modeling and architecture design, highlight specific projects where you designed data architectures. Talk about the tools you used, like Snowflake or dbt, and the impact of your design decisions on business outcomes.

To ensure high data quality and integrity, emphasize your strategies for implementing data governance frameworks, as well as techniques for monitoring data quality. Share examples of how you addressed data integrity issues in previous roles and the processes you put in place to prevent future occurrences.

Discuss your hands-on experience with cloud technologies, specifically mentioning services like AWS, GCP, or Azure. Explain how you've leveraged these platforms to optimize data management and what factors influenced your architectural decisions when deploying data solutions.

Collaboration is key, so provide a specific example where you worked with cross-functional teams such as Product, GRC, or marketing. Explain the nature of the project, your role in facilitating communication, and how your contributions helped achieve the project’s goals.

When discussing data integration and lineage strategies, describe the processes you implement to document data flow and lineage from source to target. Mention tools you have used and how you ensure transparency and traceability in your integrated systems.

Describe your approach to MDM by outlining steps you would take to assess current data needs, establish governance frameworks, and then execute the MDM implementation. Include previous experiences that illustrate your understanding of MDM best practices.

Explain how you prioritize data security and compliance by referencing legal frameworks and standards such as GDPR or CCPA. Discuss specific techniques you've used to safeguard data within your architecture while still enabling accessibility for analytics.

Share your experiences related to machine learning by discussing how you structured and cleansed data for model training. Elaborate on your understanding of data readiness for AI applications and how you optimize datasets for performance.

Your passion for learning is crucial, so mention sources you follow, such as tech blogs, webinars, or specific communities on platforms like LinkedIn. Share how you implement new knowledge or tools in your current work to keep your skills sharp.

Be prepared to discuss specific challenges you encountered in your previous roles. Reflect on how you identified the problem, the steps you took to address it, and what you learned from the experience. Focus on outcomes and any innovative solutions you implemented.