Head of Data & AI

e.l.f. Beauty•Oakland, CA

9d•$200,000 - $230,000•Hybrid

About The Position

We’re looking for a bold, visionary, and hands-on Head of Data & AI to architect and operationalize our data-driven future. This leader will shape our AI-first data strategy , build a world-class data foundation , and accelerate value creation across analytics, automation, and intelligent experiences. You’ll own the full lifecycle of our data ecosystem — from architecture to governance to AI activation — ensuring that data is not just reliable and compliant, but ready to power the next generation of business intelligence, personalization, and autonomous decision-making.

Requirements

10+ years leading enterprise data engineering, architecture, or AI initiatives.
Deep expertise in Snowflake and metadata management platforms such as Atlan , Collibra , or Alation .
Proven experience implementing data observability , lineage, and monitoring tools (e.g., Monte Carlo, Databand, Soda).
Strong understanding of data governance, privacy, and MLOps principles.
Demonstrated success building and scaling AI-ready data platforms — enabling ML pipelines, model serving, or generative AI use cases.
Experience leading cross-functional collaboration between engineering, analytics, and business teams.
Strategic mindset balanced with a bias for execution and operational excellence.

Nice To Haves

You think like a product owner for data — obsessed with usability, adoption, and measurable value.
You lead with clarity and curiosity , connecting business ambition to technical architecture.
You embrace experimentation and governance as dual engines of innovation.
You’re passionate about empowering others — turning “data consumers” into “data creators.”

Responsibilities

Lead enterprise data architecture and platforms — design and scale a modern, cloud-based data stack leveraging Snowflake , Atlan , and complementary technologies (e.g., dbt, Fivetran, Airflow).
Establish data observability and quality frameworks — ensure data lineage, reliability, and real-time insights across all systems.
Drive AI-first data strategy — enable machine learning and generative AI capabilities through structured data tagging, metadata management, and model-ready pipelines.
Partner with business and technology teams — turn data into action by collaborating across digital, marketing, finance, and operations to define use cases, KPIs, and outcomes.
Governance and compliance — define robust policies for privacy, security, and ethical AI use; partner with Legal and Security teams to align with evolving regulations.
Build and lead a high-performance global data team — recruit, mentor, and inspire data engineers, architects, and AI specialists.
Accelerate insight to impact — democratize data access, foster a culture of experimentation, and drive adoption of self-service analytics and AI tools.