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E.L.F. BEAUTY Tech Stack

Multi-brand beauty and skincare company scaling supply chain and marketing tech

Personal Care Product Manufacturing Oakland, California 201–500 employees Founded 2004 Public Company

E.L.F. Beauty operates a portfolio of four brands (e.l.f. Cosmetics, e.l.f. SKIN, Well People, Naturium, and rhode) across cosmetics and skincare, with headquarters in Oakland. The tech stack reveals a business optimizing supply chain and data infrastructure—SAP S/4HANA and NetSuite for ERP, Snowflake + dbt + Fivetran + Airflow for analytics, and Atlan for data governance—while actively adopting application security scanning (SAST/DAST/IAST), suggesting internal security maturity is accelerating. Hiring velocity is increasing, with marketing (14 open roles) and ops (9) dominating the hiring mix; this imbalance points to a company scaling brand management and supply-chain efficiency rather than engineering-led product development.

Tech Stack 93 technologies

Core StackSAP S/4HANA Snowflake Atlan dbt Fivetran Apache Airflow Swift Kotlin Java C# .NET Adobe Illustrator Adobe Photoshop Figma Adobe InDesign Canva Braze NetSuite ADP iOS Android Adobe Acrobat X Pinterest Snapchat PLM ERP Substack Photoshop Google Analytics 4+62 more
AdoptingSAST DAST IAST

What E.L.F. BEAUTY Is Building

Challenges

  • Standardize sourcing processes
  • Maintaining brand consistency across channels
  • Diversify supplier base
  • Enhancing acquisition retention
  • Driving conversions
  • Optimizing online experience
  • Improving system stability
  • Improving sourcing efficiency
  • Supplier management challenges
  • Optimize cost to improve gross margin

Active Projects

  • Predictive audience targeting
  • Master data management system development
  • Campaign launch
  • Measurement framework development
  • Social-first content strategy
  • Integrated marketing flywheel
  • Brand partnership and collaboration opportunities
  • 360° marketing campaigns across e.l.f. beauty portfolio
  • Category sourcing strategy development
  • Supplier strategies across multi-brand portfolio

Hiring Activity

Accelerating45 roles · 15 in 30d

Department

Marketing
14
Ops
9
Sales
7
Data
3
Engineering
3
Legal
3
Education
1
HR
1

Seniority

Senior
21
Manager
13
Mid
6
Director
4
Junior
1

Notable leadership hires: Sourcing Director, Sales Director

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About E.L.F. BEAUTY

E.L.F. Beauty manufactures and sells cosmetics and skincare products across multiple brands, emphasizing clean and cruelty-free formulations. The company went public and operates from Oakland, California, with 201–500 employees. Current projects center on predictive audience targeting, master data management system development, measurement frameworks, and a social-first content strategy—all oriented toward improving customer acquisition and retention. Operational pain points include standardizing and optimizing sourcing processes, diversifying suppliers, maintaining brand consistency across channels, and improving gross margins through cost optimization.

HeadquartersOakland, California
Company Size201–500 employees
Founded2004
Hiring MarketsIndia, China, Germany, United States, United Kingdom

Frequently Asked Questions

What ERP and data platforms does E.L.F. Beauty use?

E.L.F. Beauty uses SAP S/4HANA and NetSuite for enterprise resource planning, Snowflake for data warehousing, and dbt + Fivetran + Apache Airflow for data pipeline orchestration and transformation. Atlan provides data governance and catalog.

What countries does E.L.F. Beauty hire in?

E.L.F. Beauty has active hiring in the United States, United Kingdom, Germany, India, and China across marketing, operations, sales, data, and engineering functions.

How this profile is built

E.L.F. BEAUTY's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.