Engineering Operations and Analytics Engineer
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Minimum qualifications:
- Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, a related technical field, or equivalent practical experience.
- 5 years of experience in program management.
- 5 years of experience in scripting languages, specifically Python, for data manipulation, statistical analysis, and task automation, including building and maintaining automated data pipelines (ETL/ELT) to ensure data quality and availability.
- Experience in overseeing the delivery of data-driven or technical initiatives.
Preferred qualifications:
- Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field.
- 5 years of experience in semiconductor manufacturing and testing.
- Experience in manufacturing, quality, reliability, or product engineering related industries.
- Experience in advanced data visualization tools like Tableau, Power BI, or Looker, with a focus on creating actionable insights and executive-level dashboards.
- Experience overseeing the AI/ML lifecycle, including the deployment of machine learning models into production and the continuous monitoring of their performance to ensure long-term reliability.
- Familiarity with cloud platforms (e.g., Google Cloud Platform (GCP)) and their native data warehousing solutions.
About the job
A problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Technical Program Manager at Google, you’ll use your technical expertise to lead complex, multi-disciplinary projects from start to finish. You’ll work with stakeholders to plan requirements, identify risks, manage project schedules, and communicate clearly with cross-functional partners across the company. You're equally comfortable explaining your team's analyses and recommendations to executives as you are discussing the technical tradeoffs in product development with engineers.
Responsibilities
- Develop and implement data-driven solutions to improve custom silicon assembly and test manufacturing efficiency, yield, and product quality.
- Utilize statistical analysis and machine learning techniques to analyze large datasets of semiconductor production data, identify trends, and predict potential issues.
- Create automated data pipelines and dashboards to monitor Key Performance Indicators (KPIs) and provide real-time insights to stakeholders.
- Collaborate with cross-functional teams to gather data requirements, develop data analysis strategies, and communicate findings effectively.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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