Specialist, Data & AI Engineer

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The Specialist, Data & AI Engineer plays a critical role in supporting data-driven initiatives by focusing on preparing, integrating, and structuring data to build a strong foundation for business insights. This core data engineering role centers on building robust data pipelines, managing ETL processes, and developing data solutions using Python, PySpark, SQL, Azure, and Microsoft Fabric. As a secondary focus, this role supports advanced analytics by applying a basic understanding of Machine Learning and AI/LLM applications to explore and assist with various business use cases across Performance Materials. Data Engineering & ETL (Primary Focus) • Build, support, and maintain end-to-end ETL processes (Extract, Transform, Load) using SQL, Python, PySpark, and Azure Data Factory (ADF). • Execute data cleansing, transformation, and preparation to ensure high data accuracy, reliability, and consistency. • Develop and maintain robust data pipelines and structured datasets tailored for downstream analytics and business use. Data Integration & Management • Develop and maintain data models, view tables, and custom datasets utilizing SQL and Microsoft Fabric. • Collect, ingest, and integrate data from multiple diverse sources (e.g., SQL databases, APIs, Salesforce). • Ensure proper data mapping, architecture alignment, and compliance with overarching business requirements. Reporting & Automation • Develop and automate reporting workflows using SQL, Python, and Power Automate. • Maintain dashboards and reporting systems to empower business decision-making and operational efficiency. Analytics, AI & Machine Learning (Secondary Focus) • Analyze datasets to identify patterns, trends, and actionable business insights. • Apply basic knowledge of Machine Learning to assist in the development of models for use cases like customer segmentation and sales forecasting. • Support the testing and integration of AI/LLM/GPT models for business applications, including basic prompt engineering and API testing for NLP tasks. • Maintain a proactive mindset to learn and explore emerging AI technologies that can safely enhance business processes. Stakeholder Collaboration • Work closely with business stakeholders to understand requirements and translate them into scalable data solutions. • Present insights and findings in a clear and structured manner using data storytelling. • Ngày làm việc: • Giờ làm việc: • Cấp bậc: • Loại công việc: