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We are seeking a highly motivated New College Graduate to join our Data Solutions team as a Software Data Platform Engineer. In this role, you will work on the design, development, and optimization of data systems that support advanced analytics, automation, and decision-making in our manufacturing environment. You will gain hands-on experience in building data pipelines, managing large datasets, and enabling digital transformation across our operations. This position is ideal for fresh graduates who are passionate about data engineering, analytics platforms, and scalable software systems, and who want to grow their careers in a high-impact, technology-driven environment.
Job Responsibility:
Assist in the design, development, and deployment of data pipelines for structured and unstructured data
Collaborate with cross-functional teams (engineering, automation, IT, and operations) to integrate data solutions into business processes
Contribute to the implementation and optimization of data processing frameworks and tools for large-scale manufacturing datasets
Ensure data quality, consistency, and security through validation, monitoring, and documentation
Participate in data modeling, storage, and retrieval strategies to support analytics and reporting use cases
Develop and maintain technical documentation for data systems, APIs, and workflows
Stay up-to-date with emerging technologies in cloud, data engineering, and automation to support continuous improvement
Requirements:
Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field
Strong programming foundation (Python, C#, or JavaScript preferred)
Familiarity with relational databases (SQL) and data modeling concepts
Exposure to data pipelines or ETL processes through coursework, projects, or internships
Strong analytical, problem-solving, and communication skills
Eagerness to learn and adapt quickly in a fast-paced, technical environment
Nice to have:
Familiarity with big data technologies (e.g., Spark, Hadoop, Kafka)
Experience with cloud platforms (AWS, Azure, or Google Cloud)
Exposure to containerization or orchestration tools (Docker, Kubernetes)
Knowledge of manufacturing, automation, or IoT data integration
Experience with version control systems (Git) and collaborative development practices