Data Engineer
Posted Updated
Summary
Build and maintain data pipelines, enterprise data models, dashboards and Python automation for POET's enterprise data and digital transformation platform, supporting semiconductor manufacturing and supply-chain operations. Core stack: Python, SQL, ETL tools, and BI tools like Power BI/Tableau.
The Data Engineer will support the development of POET's enterprise data and digital transformation platform, working across data engineering, analytics, automation and application development, with exposure to semiconductor manufacturing and supply-chain processes.
This role suits candidates who enjoy programming, problem solving and working with data, and who want to build broad expertise in data engineering and digital transformation.
Job Responsibilities
Develop and maintain data pipelines using Python, SQL and modern data-engineering tools. Extract, transform and integrate data from databases, APIs, files, ERP and manufacturing systems. Support the development of enterprise data models and analytical datasets. Develop Python scripts, APIs and lightweight applications to automate business processes. Perform data validation, reconciliation and troubleshooting to ensure data accuracy and reliability. Build and maintain dashboards and reports using Power BI, Tableau or similar tools. Partner with business and cross-functional teams to translate requirements into technical solutions for supply-chain, manufacturing, operations and planning (APS) initiatives. Maintain technical documentation, source control and testing standards, and explore AI, machine learning and generative AI use cases where relevant. Requirements
Degree in Computer Science, Data Science, Information Systems, Engineering or a related discipline. 0-3 years of relevant experience; candidates without prior work experience but with strong technical skills are welcome to apply. Good programming skills in Python and working knowledge of SQL. Understanding of databases, data structures, software-development fundamentals and ETL/data-pipeline concepts. Strong analytical and problem-solving skills, good communication, and a proactive, ownership-oriented approach to learning new technologies. Exposure to Power BI, Tableau, cloud platforms, Git, APIs or machine learning, and interest in supply chain, manufacturing or semiconductor operations, are advantageous.
Develop and maintain data pipelines using Python, SQL and modern data-engineering tools. Extract, transform and integrate data from databases, APIs, files, ERP and manufacturing systems. Support the development of enterprise data models and analytical datasets. Develop Python scripts, APIs and lightweight applications to automate business processes. Perform data validation, reconciliation and troubleshooting to ensure data accuracy and reliability. Build and maintain dashboards and reports using Power BI, Tableau or similar tools. Partner with business and cross-functional teams to translate requirements into technical solutions for supply-chain, manufacturing, operations and planning (APS) initiatives. Maintain technical documentation, source control and testing standards, and explore AI, machine learning and generative AI use cases where relevant. Requirements
Degree in Computer Science, Data Science, Information Systems, Engineering or a related discipline. 0-3 years of relevant experience; candidates without prior work experience but with strong technical skills are welcome to apply. Good programming skills in Python and working knowledge of SQL. Understanding of databases, data structures, software-development fundamentals and ETL/data-pipeline concepts. Strong analytical and problem-solving skills, good communication, and a proactive, ownership-oriented approach to learning new technologies. Exposure to Power BI, Tableau, cloud platforms, Git, APIs or machine learning, and interest in supply chain, manufacturing or semiconductor operations, are advantageous.