Data Engineer Student - Digital & AI Solutions

Hatch develops digital and AI solutions across the Metals, Energy, and Infrastructure sectors to enable operational safety, efficiency, value chain optimization, and real-time process control and automation. Our clients are accelerating investments in data platforms, industrial IoT, cloud-native architectures, and AI-enabled applications to unlock real-time insights and improve operational performance. 

Hatch is seeking a highly motivated Data Engineer Student to join our Digital team in Mississauga, Canada. This role will play a critical part in architecting, building, and scaling robust data and AI solutions across industrial operations and enterprise value chains. 

The successful candidate will be responsible for: 

Solution Architecture Development

• Understanding and leveraging Hatch and/or clients’ existing data infrastructure, design and implement scalable, secure, and high-performance solution architectures for industrial IT/OT environments. 

• Build, configure and maintain batch and real-time data pipelines to ingest, process, and transform large-scale industrial datasets, including time-series process data and sensor data. 

• Architect data models and storage solutions across cloud and hybrid environments for AI application development. 

Software Development

• Develop production-grade software components (backend and frontend) and APIs to support AI/ML, optimization, and analytics applications. 

• Collaborate with product team and data scientists to operationalize models into scalable and maintainable production systems. 

• Design and maintain MLOps and DataOps workflows to ensure reliable deployment, monitoring, and version control of data and models. 

Industrial Systems Integration

• Integrate enterprise data platforms with industrial OT systems, including data historians, control systems, and edge computing environments. 

• Design secure IT/OT data flows, ensuring compliance with cybersecurity and network architecture best practices (e.g., DMZ structures, secure APIs). 

• Support real-time data streaming and event-driven architectures for operational decision support. 

• Collaborate with process engineers, control specialists, and client IT teams to ensure seamless integration with plant systems and enterprise applications. 

Client Engagement & Delivery Excellence

• Participate in technical architecture design sessions with clients and provide guidance on platform modernization and cloud transformation. 

• Translate business and operational requirements into robust, scalable technical solutions. 

• Support quick proof-of-value implementations and transition solutions into long-term production environments. 

• Contribute to technical documentation, architecture standards, and reusable accelerators. 

Technology & Capability Development

• Contribute to the development of standardized data pipeline, DevOps practices, AI/optimization model operationalization and application backend/frontend templates. 

• Stay current with emerging technologies in cloud/edge computing, distributed systems, data engineering, and industrial digitalization. 

Experience and Skills Important for the Role

• Year 3 or 4 Bachelor’s degree in Computer Science, Software Engineering, Data Engineering, or related field. 

• Strong programming skills in Python (required) and experience with Java, Matlab, or other programming languages is an asset. 

• Experience building and maintaining large-scale data pipelines using modern data platforms (e.g., Databricks, Azure Data Factory, etc.). 

• Hands-on experience designing and deploying solutions on cloud platforms (Azure, AWS, or GCP); Azure and/or GCP professional certifications are considered a strong asset. 

• Experience designing RESTful APIs, frontend-backend interaction, microservices architectures, and containerized applications (Docker, Kubernetes). 

• Hands-on experience implementing CI/CD pipelines and DevOps practices (Git, Azure DevOps, GitHub Actions, etc.). 

• Experience with modern frontend frameworks (e.g., React, etc.) for building data-driven web applications and understanding of responsive UI design principles is an asset. 

• Knowledge of database technologies including SQL, NoSQL, and time-series databases. 

• Familiarity with industrial IT/OT environments, data historians (e.g., PI systems), real-time integration, and cybersecurity considerations is an asset. 

• Strong problem-solving mindset and ability to design scalable solutions for complex industrial challenges. 

• Proven ability to collaborate effectively across multidisciplinary teams. 

• Multilingual capability in English, Spanish, and/or Portuguese is an asset, particularly for collaboration across global client operations.