About the Role
This position leads data engineering efforts in intelligent manufacturing, focusing on creating robust, scalable data infrastructure that enables real-time analytics, process optimization, and advanced monitoring across production environments.
Responsibilities
- Design and implement scalable data pipelines for high-volume manufacturing data streams
- Develop and maintain ETL workflows for real-time and batch processing systems
- Collaborate with manufacturing engineers to identify data needs and integration points
- Build data models that support predictive maintenance and quality analytics
- Ensure data accuracy, consistency, and traceability across production systems
- Integrate data from shop floor sensors, control systems, and enterprise platforms
- Optimize data storage and query performance in cloud and on-premise environments
- Support data governance and metadata management practices
- Work with cross-functional teams to deploy machine learning models in production
- Troubleshoot and resolve data pipeline issues with minimal downtime
- Document data architectures and integration patterns for team reference
- Evaluate and recommend new data technologies and tools
- Ensure compliance with data security and privacy standards
- Participate in agile development cycles and sprint planning
- Mentor junior engineers and contribute to team knowledge sharing
- Monitor system performance and implement improvements proactively
- Support root cause analysis using data-driven insights
- Collaborate on data strategy initiatives for smart factory evolution
- Implement data validation frameworks to ensure input integrity
- Work with global teams to standardize data engineering practices
Nice to Have
- Master’s degree in computer science, data science, or engineering
- Experience with edge computing in manufacturing contexts
- Familiarity with digital twin architectures
- Knowledge of time-series databases and their optimization
- Experience with data visualization tools such as Grafana or Power BI
- Exposure to machine learning operations (MLOps) in production systems
- Certifications in cloud data platforms or data engineering
- Background in automotive or heavy manufacturing industries
- Contributions to open-source data projects
- Leadership experience in technical project delivery
Compensation
Competitive salary and benefits package
Work Arrangement
Hybrid work model with flexibility based on location and role requirements
Team
Part of the global data and analytics team driving digital transformation in manufacturing operations
Why This Role Matters
- Manufacturing operations generate vast amounts of data that, when properly harnessed, can drive efficiency, reduce waste, and improve product quality. This role is central to transforming raw industrial data into actionable insights.
- As manufacturing systems become more connected and intelligent, the need for reliable, high-performance data pipelines grows. This position ensures data is available, accurate, and ready for advanced use cases such as AI-driven quality control.
What You’ll Bring
- A strong foundation in software engineering with a focus on data-intensive systems.
- Experience working in industrial or operational technology environments.
- A collaborative mindset with the ability to work across technical and functional teams.
Available for qualified candidates requiring sponsorship
