Vice President of Engineering
This is a hybrid role to be based near one of our offices in New York City, Austin or Los Angeles.
About the Role
The VP of Engineering is a senior leadership role responsible for the full engineering organization at Material, spanning software, data, AI/ML, solutions architecture, product, design, QA, and insights operations. Reporting to executive leadership, you will own the technical strategy, org design, delivery model, and engineering culture across a multi-cluster team operating across multiple time zones — including offshore engineering talent.
This is a hands-on leadership role. You will shape how we build, scale, and modernize our core platforms — from survey data collection and processing pipelines to AI-powered reporting tools and client-facing solutions — while simultaneously building the operational model that makes our engineering teams more effective at every level.
Key Responsibilities:
Technical Strategy & Architecture
- Define and evolve the technical architecture across data, software, AI/ML, and infrastructure layers — with particular emphasis on cloud-native and lakehouse patterns (medallion architecture, parallelism, datalake)
- Lead modernization efforts to retire and replace legacy applications and tech stacks with scalable, maintainable alternatives
- Maintain a forward-looking product and infrastructure roadmap, balancing innovation initiatives against operational reliability and delivery commitments
- Champion Infrastructure-as-Code practices (Terraform, AWS CDK) and platform engineering standards across all engineering clusters
Engineering Leadership & Org Design
- Lead and develop a cross-functional engineering organization structured around delivery clusters, including Technical Product Leads, senior engineers, and offshore pod teams
- Hire, develop, and retain top engineering talent; define role frameworks, competency ladders, and technical career paths
- Foster a high-accountability, delivery-focused engineering culture grounded in clear ownership, psychological safety, and continuous improvement
- Manage distributed teams across multiple timezones, ensuring effective communication, alignment, and productivity across offshore and onshore resources
Product & Business Alignment
- Partner with operations and business leadership to translate ambiguous business requirements into well-scoped engineering initiatives
- Work closely with product and project managers to maintain a prioritized, resourced backlog that balances client commitments, internal tooling, and strategic modernization
- Serve as the primary technical voice in executive discussions, providing clear signal on feasibility, tradeoffs, capacity, and risk
- Define and uphold integration contracts and delivery standards between engineering clusters and adjacent operational functions
Delivery & Operations
- Own engineering delivery health: velocity, quality, incident response, and continuous improvement rituals across all teams
- Establish/Evolve standards across workflow management (Jira, Confluence), data orchestration, and QA
- Drive adoption of AI/ML capabilities across both internal tooling and client-facing product features
- Oversee vendor relationships, licensing decisions, and build-vs-buy evaluations for platform tooling and infrastructure services
Required Qualifications:
- 8+ years of combined experience in Data, Software, and Product Development, with at least 4 years in senior engineering leadership
- Multi-cloud expertise across AWS, GCP, and Azure — with the ability to evaluate tradeoffs and select the right platform for each workload
- Infrastructure-as-Code proficiency with Terraform and/or AWS CDK
- Cross-functional team leadership across multiple time zones, including offshore engineering teams
- Business requirements translation — proven track record triaging with operations and engineering leaders, working in lockstep with product/project managers on prioritization and resourcing
- Advanced Snowflake experience including performance optimization, data sharing, and exposure to AI/ML services (Cortex, Snowpark)
- Broad engineering fluency across data engineering, software engineering, AI/ML, UI/UX, and QA — able to credibly engage with practitioners across all disciplines
- Legacy modernization leadership — experience assessing, sequencing, and communicating large-scale platform migrations to technical and non-technical stakeholders
Nice-to-Have Qualifications:
Data & Analytics Platforms
- Lakehouse architecture experience with Apache Iceberg, Delta Lake, or equivalent open table formats
- Survey/research platform familiarity — Dimensions, Unicom Intelligence, or comparable platforms
- Identity resolution and data governance — deduplication, consent frameworks, and PII handling at scale
AI/ML & Emerging Technology
- AI agent development — experience architecting or overseeing agentic workflow systems
- Synthetic research or behavioral data pipelines in a research or insights context
- Fraud detection, statistical weighting, and automated testing integrated into data products
Cloud & Infrastructure Depth
- AWS service depth — Step Functions, Lambda, EMR, ECS, Athena, Zero-ETL, S3-based lakehouse patterns
Leadership & Business
- Research, insights, or data-as-a-service business context experience
- Budget ownership — headcount planning, vendor negotiation, and CapEx/OpEx tradeoffs
- Hiring infrastructure — building assessments, job descriptions, and interview frameworks for mid-to-senior engineering roles
- Executive communication — comfortable presenting technical strategy to C-suite and board-level stakeholders
PayRange:$180,000.00 60,000.00
The range shown represents a grouping of relevant ranges currently in use at Material. Actual range for this position may differ, depending on location and specific skillset required for the work itself.
