Analytics Engineer
EspooCompetitive0 applicants
About this role
Silicon Labs (NASDAQ: SLAB) is the leading innovator in low-power wireless connectivity, building embedded technology that connects devices and improves lives. Merging cutting-edge technology into the world's most highly integrated SoCs, Silicon Labs provides device makers the solutions, support, and ecosystems needed to create advanced edge connectivity applications. Headquartered in Austin, Texas, Silicon Labs has operations in over 16 countries and is the trusted partner for innovative solutions in the smart home, industrial IoT, and smart cities markets. Learn more at www.silabs.com.
Responsibilities
- We are looking for an Analytics Engineer to join us in the Business Operations & Analytics team in our Data & Sales Operations. The team provides analytics services across multiple domains in Silicon Labs including Sales, Product Lines, Customer Support and other business functions. The team also works closely with other analytics functions in eg. Operations and R&D. Other team members include data analysts and data scientists.
- Analytics solutions Technical design and delivery of analytics solutions
- Project management and design
- Stakeholder management
- Technical leadership
- Ownership of best practices for code-based analytics
- Coach team members
- Evaluate and contribute to data & analytics architecture and tool selection
- Key Requirements
- 4+ years of progressive experience in analytics
- Master's degree in a quantitative field
- Able to provide good technical solutions to any data & analytics problem
- Able to focus on business value in analytics solutions
- Advanced skills in Python & SQL
- Good understanding of utilizing GenAI
- Good understanding of modern cloud-based data & analytics tools and architecture
- Good understanding of data architecture principles and data modeling
- Strong teamwork skills and ability to function in a diverse & international environment
- Excellent communication skills in English
- The following are beneficial:
- Experience with Databricks an