Staff NPI Data Analytics Engineer
$170k/y-$210k/y
Credoa day ago
Highlight
OnsiteFull-timeSenior
Summary
Credo is seeking a Staff NPI Data Analytics Engineer to join their team in San Jose, CA. The role focuses on optimizing New Product Introduction (NPI) workflows and high-volume manufacturing operations through data analytics.
About the Role
As a Staff NPI Data Analytics Engineer, you will be responsible for ensuring seamless data analytics, robust Bill of Materials (BOM) management, and complete product lifecycle traceability across advanced components. You will collaborate with internal test, characterization, and manufacturing teams, as well as external component suppliers, to maintain high-quality data flow from development through production. The position requires approximately 25% international travel and involves championing data analytics tools to model performance and validate process capabilities.
About You
Required:
- Bachelor’s degree in engineering, Computer Science, Data Science, or a related technical field.
- 7+ years of progressive experience in R&D, NPI, and/or Manufacturing Engineering, technical program management, validation, test systems, or data platforms.
- Hands-on experience in data analytics for development and manufacturing.
- Proficiency with tools such as Python, JMP, advanced Excel, or Minitab.
Preferred:
- Strong understanding of data pipelines, schema governance, KPI frameworks, and analytics systems.
- Experience with AI/ML logic models in development and manufacturing data analytics.
- Proven ability to work with internal test/characterization teams and external suppliers.
- Effective communication skills across global and multicultural teams.
Benefits
- Base salary range of $170k–$210k per year.
- Eligible for discretionary bonus and equity.
- Full range of medical and other benefits.
Credo
Credo’s mission is to advance high-speed connectivity solutions that deliver optimized performance, reliability, energy efficiency, and security for the next generation of AI-driven applications, cloud computing, and hyperscale networks.
San Jose, CA