Lead Data Platform Engineer

Virtuous develops software for nonprofits and is building an AI-ready data foundation to support trusted decision-making and self-service analytics. The Lead Data Platform Engineer will own the evolution of the company’s Snowflake and dbt data platform, focusing on governed access, AI enablement, reliability, cost optimization, and reusable platform capabilities.

Responsibilities:

• Own the evolution of Virtuous’s data platform, primarily on Snowflake and dbt, as a secure, scalable, and AI-ready system
• Design data models, metadata, and access patterns that support natural-language querying and AI-assisted analysis
• Partner with Data Operations and Teams across the company to ensure data structures are accurate, reusable, and aligned with business definitions
• Prepare data foundations that allow AI tools to deliver consistent, timely, and trustworthy answers
• Ensure AI systems access data exclusively through governed service accounts and role-scoped permissions, with query activity auditable and restricted according to enterprise data classification and access standards
• Architect and implement role-based access controls within Snowflake and related data systems (including row- and column-level security), ensuring enforcement aligns with enterprise IAM standards, approved access policies, and centralized identity governance processes
• In partnership with Security Operations and IT, translate approved enterprise access and compliance policies into enforceable platform-level controls, and maintain technical configurations to ensure ongoing alignment with those standards
• Ensure all platform-level access controls integrate with the enterprise identity provider (SSO, SCIM, role lifecycle management), and support automated provisioning, deprovisioning, and periodic access certification processes
• Build governance patterns that are enforced by design — not by manual process
• Support periodic access reviews and control validation processes in coordination with Security and Compliance teams, ensuring appropriate separation of duties between policy definition, approval, and technical implementation
• Build and maintain CI/CD pipelines, testing strategies, and deployment patterns for dbt and Snowflake
• Design deployment, testing, and validation patterns that make accuracy the default
• Establish platform standards, templates, and best practices that enable others to move faster without sacrificing quality or security
• Increase the amount of trusted work the organization can do without increasing Data Ops involvement
• Reduce ad hoc work by building reusable systems and guardrails
• Act as a technical leader and thought partner across data-related initiatives
• Own Snowflake warehouse strategy, resource governance, and cost optimization
• Continuously improve performance, scalability, and reliability across the data platform
• Identify and eliminate inefficiencies that increase cost, risk, or operational overhead
• Collaborate with IT and Cloud Engineering to ensure Snowflake networking, storage integrations, and data movement patterns align with enterprise cloud security baselines, network segmentation standards, and infrastructure governance policies

Requirements:

• 7+ years of experience in data engineering, platform engineering, or related infrastructure roles, with ownership of production systems
• Deep expertise in Snowflake, especially:
• Roles and RBAC
• Row-level and column-level security
• Warehouse design and cost optimization
• Performance tuning and governance
• Strong experience using dbt to build and maintain shared data models, including macro development, testing strategies, source freshness, group model security implementation, and production deployment patterns
• Advanced SQL skills and experience designing reliable ELT/ETL pipelines
• Proven systems-thinking mindset, with the ability to reason about tradeoffs across correctness, access, cost, and speed
• Clear communicator who can explain complex technical concepts to both technical and non-technical partners
• dbt certification strongly preferred
• Experience enabling AI/ML or natural-language data access
• Familiarity with data observability, lineage, or metadata tooling
• Experience designing platforms for self-service analytics
• Exposure to BI tools such as Sigma, Looker, or Tableau
• Experience working in lean, fast-growing organizations where leverage matters more than headcount