Data Warehouse & Analytics Architect

About Virtru: While the rest of the security industry focuses on locking down data to prevent loss or theft, Virtru reimagines security by enabling intentional data sharing without compromising privacy or control. We’ve built a powerful data protection platform and an open ecosystem through the Trusted Data Format (TDF) standard, fostering innovation while ensuring security.

Backed by top-tier investors like Iconiq Capital and Tiger Global, Virtru empowers Fortune 500 companies and government agencies to share data securely, collaborate freely, and innovate confidently.

Compensation: $180,000–$220,000/year

Role Overview: Virtru is seeking a Data Warehouse & Analytics Architect with 7+ years of SRE experience to lead architectural excellence and technical mentorship for our digital privacy products. This player/coach role blends architecture, design, and hands-on implementation, partnering with engineering teams to scale mission-critical data infrastructure securely.

Core Responsibilities:

Software Architecture & Design:

• Lead system design and architecture reviews for scaled data warehouses and deploy web-scale data analytics applications.
• Leverage SRE principles to deploy data and AI analytics applications at scale across clouds.
• Create and maintain architectural documentation, including ADRs (Architecture Decision Records).
• Design data lakehouse architectures, data modeling, and integration patterns for scalable databases and data-as-a-service solutions.
• Provide technical direction for scaling complex data storage, processing, and deployment initiatives.
• Familiarity with DevSecOps, AIOps, and MLOps required.

Technical Health & Quality:

• Monitor and reduce technical debt across data storage, processing, and SRE systems.
• Partner with Engineering Managers to define technical health metrics and streamline onboarding.
• Drive reliability, performance, and security best practices for data infrastructure.
• Break down complex tasks into manageable deliverables for the team.
• Ensure sustainable engineering practices and code quality standards.
• Act as a technical guide for data access, storage, and deployment architecture.
• Align teams with current and future architectural designs.

Technical Leadership & Mentorship:

• Mentor engineers on data storage, warehouse, processing, and SRE systems.
• Lead by example with high-quality code contributions to critical components.
• Share expertise in hyperscale data warehouses/lakehouses, data models, and emerging technologies.
• Assist SRE teams with stability, automation, and scalability improvements.
• Conduct code reviews focused on architectural alignment.
• Support hiring processes and technical assessments.

Collaboration & Strategic Partnership:

• Collaborate with Engineering Managers, Product Management, UX, and other architects to design solutions.
• Resolve cross-team dependencies and technical challenges.
• Align technical roadmaps with product and business priorities.
• Participate in platform-wide architectural initiatives.

Execution:

• Own the entire lifecycle of data components from design to deployment.
• Balance hands-on coding with architectural responsibilities.
• Work in a fast-paced, collaborative environment across projects.
• Build software impacting data privacy approaches.

Required Skills:

• Cloud data warehouses (BigQuery, Redshift, Synapse, Snowflake).
• Lakehouse platforms (Apache Iceberg, Databricks, Delta Lake, Hudi).
• Data modeling (Kimball, Data Vault, dimensional).
• Columnar storage (Parquet, ORC).
• Batch and stream processing architectures.
• AI analytics at scale.
• SRE principles and infrastructure as code (Terraform).
• Containerization and orchestration (Kubernetes).
• Monitoring tools (Datadog, Prometheus, Grafana).
• CI/CD pipelines and DevOps practices.

Leadership Skills:

• Proven architectural leadership and technical influence.
• Technical mentoring and coaching experience.
• Architectural documentation and technical specifications.
• Improving technical health metrics and reducing debt.
• Cross-team collaboration and dependency management.

Education & Experience:

• Bachelor’s degree in Computer Science, Engineering, or related field.
• At least 7 years of data warehouse, database, or analytics experience.
• Architectural or technical leadership experience.

Preferred Qualifications:

• Microsoft 365 add-ins with security/UX focus.
• Data privacy, encryption, and zero-trust security knowledge.
• Open-source contributions or community involvement.

Culture Fit:

• Thinking outside the box to challenge teams for excellence.
• Action-oriented mindset with adaptability.
• Comfortable with asynchronous communication (Slack, email, Zoom).