Major Responsibilities And Tasks Of The Position
- Define and evolve scalable data architectures, platforms, pipelines, and curated data products that support manufacturing, analytics, reporting, and AI/ML applications.
- Lead the design, development, optimization, and delivery of complex ETL/ELT pipelines and distributed data-processing solutions.
- Establish and promote Data Engineering standards, development patterns, data-quality frameworks, observability practices, documentation, and platform governance.
- Provide technical leadership across projects and teams through architecture reviews, mentoring, troubleshooting, code reviews, and cross-functional collaboration.
- Partner with manufacturing, analytics, Decision Intelligence, IT, architecture, application, and business teams to align data solutions with strategic priorities.

What do you need to have?
- Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or another related technical discipline.
- At least 5 years of experience in Data Engineering, including designing, building, optimizing,



and maintaining production data pipelines, data warehouses, data lakes, or lakehouse environments.
- At least 5 years of professional programming experience using Python, with the ability to write clean, testable, maintainable, and scalable code.
- Strong hands‑on experience building data pipelines and working with Apache Spark, PySpark, SparkSQL, or comparable distributed data‑processing technologies.
- Experience working with manufacturing, production, industrial, operational, equipment, quality, supply‑chain, sensor, or time‑series data.
- Demonstrated technical leadership, including leading projects, defining architecture or engineering standards, mentoring engineers, and influencing technical decisions.
- Advanced SQL, data modeling, and database experience across relational databases, data warehouses, data lakes, or modern cloud data platforms.
- Cloud‑platform experience using AWS, Azure, or

📌 Lead Data Engineer (Monterrey)
🏢 Corning
📍 Monterrey