Required: Strong knowledge of Python and packages for data analytics and data engineering. Strong hands-on experience with visualization software like Tableau, Power BI, and JMP. Strong knowledge of REST API systems in Python such as FastAPI or Django. Strong knowledge of a UI framework, preferably Angular with Bootstrap. Hands-on experience in database technologies including SQL, Snowflake, and GCP BigQuery for setting up visualizations and business reports. Good understanding of data engineering concepts like ETL/ELT, data warehousing, and feature stores. Knowledge of descriptive and inferential statistics. Experience working in global cross-functional teams across time zones. Experience with Agile workflow and tools like Jira and Confluence. Understanding of Machine Learning and AI Algorithms and evaluation techniques for model efficiency and effectiveness. Knowledge of DevOps on cloud (GCP) or on-prem (OpenShift). Experience working with semiconductor manufacturing or deep tech manufacturing data. Knowledge of manufacturing quality practices and systems. 0-3 years of experience in data analytics or data engineering roles. Bachelor's or Master's degree in Computer Science, Software Engineering, Electrical or Electronics Engineering, or a related field with extensive programming exposure. A Master's degree is preferred. Additional qualifications such as certifications in Data Engineering, Machine Learning, Artificial Intelligence, Big Data, or notable achievements in Kaggle competitions will be considered advantageous. Develop and maintain data ETL/ELT pipelines. Develop and maintain lightweight full-stack applications using FastAPI and Angular. Develop and maintain Tableau/Power BI dashboards. Support extended teams with data-related tasks such as data extraction, analysis, and visualization. Support the team in troubleshooting and debugging issues in deployed systems. Translate business problems into data solutions. Collaborate with cross-functional teams to create impactful projects.
