Job Description

Envision Employment Solutions is currently looking for a Data & AI Engineer for one of our partners, a global leader in the chemical industry field.

Job Summary:

The Data & AI Engineer is responsible for designing, building, and maintaining the data infrastructure, pipelines, and AI solutions necessary to support the company's business needs. This role combines expertise in data engineering and applied AI to enable scalable data processing, advanced analytics, and machine learning capabilities. The engineer will work with large datasets, optimize data flows, and deliver AI-driven solutions that enhance decision-making and operational efficiency.



The ideal candidate brings extensive experience in data engineering and a strong technical background in data architecture and ETL processes. They demonstrate a deep understanding of data governance and best practices, with a proven ability to manage large-scale data environments. The candidate excels in collaboration, problem-solving, and driving continuous improvement in data engineering practices.

Responsibilities:

Design, develop, and maintain data pipelines to support data integration, processing, and AI/ML workflows. Ensure data quality, integrity, and security across all data and AI systems. Develop and implement ETL processes to ingest data from diverse sources for analytics and machine learning. Optimize data storage, retrieval, and AI model serving for performance and scalability. Collaborate with data scientists and analysts to provide high-quality datasets, features, and infrastructure for analytics, reporting, and AI experimentation. Build, deploy, and maintain AI/ML models to solve business problems, automate processes, and enhance decision-making. Implement and maintain data governance, model governance, and MLOps best practices. Monitor and troubleshoot data pipelines, AI models, and ML workflows to ensure reliability, accuracy, and efficiency. Support data-driven and AI-driven initiatives by enabling timely access to trusted data and scalable AI solutions. Develop and maintain documentation for data processes, AI pipelines, and deployed models. Stay up to date with emerging data and AI technologies, tools, and industry best practices. Ensure compliance with data protection regulations, ethical AI principles, and internal policies. Provide training and support to stakeholders on data systems, AI capabilities, and best practices. Lead efforts to continuously improve data infrastructure, AI platforms, and automation processes. Collaborate with IT, business units, and functional teams to align data and AI initiatives with organizational goals.

Requirements:

Bachelor's degree in computer science, Information Technology, Data Science, or a related field. Proven experience of at least 5+ years in data engineering, 2+ years in AI engineering, with a focus on building and maintaining data & AI pipelines in a CoE or Specialist role. Proven experience in developing and implementing ETL processes. Strong background in data architecture and Azure technologies. In-depth knowledge of data governance and data quality management principles. Excellent written and verbal English language proficiency

Skills:

Demonstrated expertise in designing, maintaining, and optimizing data pipelines, AI pipelines, and infrastructure. Strong technical knowledge of ETL processes, data integration, and MLOps using Microsoft Fabric or Azure tools. Proficiency in programming languages (e.g., Python, Java, SQL) for data processing, as well as AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience in developing, deploying, and scaling machine learning models in production environments. Excellent problem-solving and analytical skills, with a proactive approach to identifying and addressing data and AI challenges. Strong communication and interpersonal skills, able to engage effectively with stakeholders at all levels and explain AI-driven insights in business terms. Adept at managing multiple projects and priorities in a dynamic environment, including data and AI initiatives. Proficiency in data governance, model governance, and data quality management principles. Strong understanding of data protection regulations, compliance requirements, and ethical AI practices. Experience in troubleshooting and resolving data and AI-related issues, including pipeline failures and model drift. Ability to provide training and support on data systems, AI tools, and best practices. Adaptable and agile mindset towards continuous improvement, staying current with evolving data, cloud, and AI technologies. Strong analytical skills to interpret data, evaluate model performance, and predict trends for business advantage. Ability to work closely with team members, management, senior leadership, and cross-functional teams to deliver data- and AI-driven value. * Excellent verbal and written communication skills in English, with the ability to articulate and present complex technical and AI concepts clearly and concisely.