Virtuous Logo

Virtuous

Lead Data Platform Engineer

Reposted 6 Days Ago
In-Office or Remote
Hiring Remotely in USA
Senior level
In-Office or Remote
Hiring Remotely in USA
Senior level
The Lead Data Platform Engineer will design and build Virtuous's data platform, ensuring it is secure, scalable, and AI-ready. Responsibilities include architecting access controls, optimizing performance, and enabling self-service analytics while maintaining governance and compliance standards.
The summary above was generated by AI

Position Summary

Virtuous is evolving its data platform into an AI-ready foundation that powers trusted decision-making and self-service analytics across the company.

We’re hiring a Lead Data Platform Engineer to design, build, and own the systems that power our data ecosystem. This role is ideal for a highly motivated self-starter who is comfortable with ambiguity and thrives at the intersection of systems design, business semantics, and AI enablement.

This is not a traditional data engineering role focused on building one-off pipelines, dashboards, or ad hoc reports. Success in this role comes from designing and building durable platform capabilities — security models, access patterns, cost controls, and shared data foundations — that enable teams (and AI systems) to safely and confidently use data at scale.

You’ll work closely with the Director of Data Operations as well as our Finance, Product, Engineering and Security Teams to ensure our data platform is accurate, governable, and ready to support AI-enabled workflows across the company.

What You'll Build & Own
Data Platform & AI-Enablement
  • 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.

Access, Trust & Governance by Design
  • 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.

Platform Leverage & Standards
  • 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.

Reliability, Cost & Performance
  • 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.

What Success Looks Like
  • Teams reliably self-serve data and insights without increasing DataOps workload or risk.

  • AI-powered tools consistently answer business questions accurately, using governed data, with access enforced by role and context.

  • Data access, governance, and correctness are enforced by platform design rather than manual review or process.

  • Platform improvements materially reduce cost, operational risk, or time-to-insight.

  • Shared, trusted models replace bespoke datasets and one-off definitions.

  • At least one company-critical initiative (e.g., AI enablement, cost optimization, access expansion) succeeds specifically because of systems you designed and built.


Who This Role is For
  • Care about leverage, durability, and outcomes — not just shipping artifacts.

  • Think deeply about how AI and automation change the role of data platforms.

  • Are highly self-directed and motivated, and take pride in ownership.

  • Thrive in ambiguity and are comfortable making decisions with incomplete information.

  • Are motivated by leverage, correctness, and long-term impact — not ticket volume or titles.

  • Readily navigate cross-functional tradeoffs to build shared data foundations that serve the whole company, not individual teams.

You Must Have
  • 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.

Nice to Have
  • 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.

About Us

Virtuous software is powering the world’s leading nonprofits and inspiring a new generation of generosity.

At Virtuous, we believe generosity has the power to transform the world - and so we are on a mission to create $10B in net new generosity by helping nonprofits better connect with and inspire their donors.

Our talented team is hungry, humble, and committed to delivering best-in-class software solutions, customer success interactions, and sales experiences to the nonprofit community.

Our values are more than just a poster on the wall. Instead, our mission and values are precisely why candidates choose Virtuous. Our core values are:

  1. Build Better: We build audacious ideas to accelerate philanthropy and dismantle the status quo.

  2. Display Radical Generosity: We are generous with our time & talent as we serve our team and the nonprofit community.

  3. Stay Humble & Enjoy the Journey: We take our work seriously, but we don't take ourselves too seriously.

Virtuous should act as a career accelerator for everyone on our team. Team members should look back at their time at Virtuous as one of the most productive and stretching seasons in their professional lives. This means that working at Virtuous isn't for everybody. It is for the select few who are ready to do hard things and build something truly great.

If this sounds like you, we’d love for you to apply!

What We Offer
  • Market competitive pay leveraging Carta data

  • Employee recognition through Bonusly (birthdays, anniversaries, achievements, etc.)

  • 401(k) retirement plan with company matching- 50% match up to 6% of compensation after 90 days

  • We value our employee’s work-life balance and encourage taking advantage of Unlimited PTO

  • Supportive time off including paid volunteer days and company holidays

  • Employer-contributed healthcare benefits, encompassing medical, dental, and vision coverage, with plans available for dependents and choices for Health Savings Accounts (HSA) and Flexible Spending Accounts (FSA).

  • 12 weeks primary parent leave, 4 weeks secondary parent leave - full pay (adoption as well)

  • We pride ourselves on Community and host exciting company outings and events.

We’ve recently noticed an increase in recruitment scams where individuals are impersonating recruiters to obtain personal or financial information through fraudulent interviews and job offers.
Please note that all legitimate communication from Virtuous will only come from the @virtuous.org domain. If you receive a message from other domains, even if they look similar (e.g., virtuouscareers.org or virtuousjobs.com), they are not legitimate and we recommend disregarding it immediately.

Similar Jobs

5 Days Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
170K-205K Annually
Senior level
170K-205K Annually
Senior level
Fintech • Financial Services
Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.
Top Skills: Agentic Ai Coding ToolsAirbyteAmazon AuroraAWSAzureEltETLFivetranGCPInformaticaInfrastructure As CodeObservabilityPostgresReverse-EtlRuby On RailsSQL
7 Minutes Ago
Remote or Hybrid
104K-130K Annually
Mid level
104K-130K Annually
Mid level
Aerospace • Artificial Intelligence • Cloud • Machine Learning • Software • Cybersecurity • Defense
Leads mechanical design and systems integration for aerospace turbomachinery, heat transfer products, and environmental control systems. Develops manufacturable designs using Siemens NX, Teamcenter, GD&T, tolerance analysis, materials knowledge, and manufacturing-process expertise. Coordinates priorities with customers, supports supplier and production issue resolution, advances digital product definition, improves design processes through automation and AI-enabled methods, and mentors less-experienced designers.
Top Skills: Ai-Enabled Design AutomationAsme Y14.5CadDigital EngineeringGd&TPlmSiemens NxSiemens TeamcenterTolerance Stack-Up Analysis
9 Minutes Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
155K-260K Annually
Senior level
155K-260K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Build automated reliability and self-healing platform tooling to protect production at scale. Improve incident management, reduce alert noise, evolve observability (monitoring, SLOs, performance detection), and develop AI-driven operational automation. Partner with product teams to diagnose reliability gaps, drive incident prevention, and champion operational excellence and best practices across engineering.
Top Skills: AIAWSDatadogGCPGoGrafanaIncident.IoNew RelicObservabilityPagerdutyPythonSloTerraform

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account