Are you ready to take ownership of complex data solutions and help shape the future of manufacturing analytics, artificial intelligence, and data-driven decision-making? Join Corning's Optical Communications team and help build scalable, reliable, and high-quality data products that support manufacturing, operations, analytics, and AI/ML applications across a general organization.

What is your role?

As a Senior Data Engineer, you will design, build, optimize, and maintain scalable data pipelines, curated datasets, and cloud-based data solutions supporting Corning's manufacturing and operational environments.

Responsibilities
- Design, build, optimize, and maintain scalable ETL/ELT pipelines and data solutions for batch and near-real-time use cases.
- Develop reliable, production-ready datasets that support manufacturing visibility, operational decision-making, analytics, reporting, and AI/ML applications.
- Implement automated data-quality checks, monitoring, observability, and validation processes to improve data reliability and reduce production issues.




- Lead the technical delivery of complex Data Engineering projects, including solution design, development, testing, deployment, troubleshooting, and continuous improvement.
- Collaborate with manufacturing teams, analysts, data scientists, product owners, architects, application teams, and business stakeholders.
- Mentor Data Engineers through code reviews, technical guidance, troubleshooting support, and engineering best practices.

What do you need to have?
- Bachelor's degree in Computer Science, Engineering, Statistics, Mathematics, or another related technical discipline.
- At least 3 years of experience in Data Engineering or a related data-focused role, including designing, building, maintaining, or supporting production data pipelines.
- At least 2 years of hands-on professional experience using Python and building data pipelines in a production environment.
- Strong hands-on experience with Apache Spark

📌 Sr. Data Engineer (Monterrey)
🏢 Corning
📍 Monterrey