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AvernaPosted 1 month ago

Data Analyst (English version)

RemoteCanada

Full TimeMedium

Job Summary

Extract, transform, and analyze fleet-scale manufacturing, testing, and deployment data using advanced SQL. Translate complex manufacturing and quality concepts into data-driven metrics, intelligent dashboards, and AI-enabled applications. Identify opportunities to automate manual workflows and develop AI-driven recommendation systems for anomaly detection and quality insights. Design interactive reports in Looker Studio, Tableau, or Power BI to visualize operational metrics and prepare executive-level summaries. Partner with engineers and product teams to embed AI capabilities into hardware NPI and manufacturing processes while providing technical guidance on data standards and warehousing solutions.

Required Qualifications

  • Bachelor's degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics, Engineering, or a related discipline.
  • Advanced proficiency in SQL with strong understanding of data modeling and normalization best practices.
  • Proficiency in Python (or R) for data analysis, including experience with the PyData stack (NumPy, Pandas, Matplotlib, scikit-learn).
  • Strong analytical, problem-solving, and statistical analysis skills.
  • Proven experience creating dashboards, reports, and structured datasets to support business and engineering decisions.
  • Excellent verbal and written communication skills in English.

Desired Qualifications

  • 5+ years of experience working with cloud data warehouses such as Google BigQuery or equivalent platforms.
  • Familiarity with Google Cloud data products (Vertex AI, Colab, Cloud APIs).
  • 5+ years of experience building interactive dashboards in Looker Studio, Tableau, Power BI, or similar tools.
  • Practical experience with AI/ML models, Large Language Models (LLMs), and AI-enabled workflow automation.
  • Domain experience in electronics manufacturing processes, quality engineering, test engineering, or reliability engineering.
  • Exposure to data governance, data quality management, or master data management concepts.
  • Familiarity with operational topics such as headcount planning, resource allocation, or vendor/contractor (TVC) tracking.
  • Fluency in English, Mandarin or French is a plus.

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