The Data Engineer will work with our Optical Communications business, inclusive of fiber, cables, and connectivity. Their primary responsibility will be to provide robust and scalable data pipelines, reliable infrastructure, and high-quality data platforms that support manufacturing, operations, and business data users in order to enable fast, accurate insights, improve production visibility, support data‑driven decision making, and drive business value through trusted, accessible data. In addition, this role will contribute to advancing AI/ML-enabled data management capabilities within the Data Management Organization. This includes supporting AI-driven Data Quality Agents, intelligent data observability, and advanced automated data quality checks that are actively being built and expanded within the group, with a focus on manufacturing and operational data environments. Responsibilities Build and maintain data pipelines — Develop, test, and support reliable data pipelines that ingest, transform, and deliver manufacturing, operational, and business data for batch and near real‑time use cases. Support data platform operations and continuous improvement — Help maintain data infrastructure and workflows to ensure data availability, performance, and reliability for reporting, analytics, downstream applications, and AI/ML use cases. Assist with troubleshooting data issues, improving pipeline efficiency, documenting data flows, and following engineering best practices for maintainable and scalable data solutions. Implement data quality processes — Apply automated checks, validation rules, and monitoring to help ensure the accuracy, completeness, and consistency of manufacturing and operational data, while supporting data readiness for AI‑driven analytics and machine learning applications. Develop production‑ready datasets — Work with manufacturing teams, analysts, data scientists, and other business partners to understand data needs and deliver clean, usable datasets that support reporting, analysis, operational decision‑making, and AI/ML model development. Support AI/ML data integration — Prepare, transform, and structure manufacturing and operational data for AI/ML use cases, including enabling model training, feature development, inference workflows, and data availability for intelligent monitoring and automation solutions. Career Growth Data Engineer SME Path — For individuals whose passion is deep technical mastery and subject‑matter expertise Build strong expertise in data platforms, pipelines, and domain‑specific data, with opportunities to become a go‑to resource for specific systems or manufacturing data domains Contribute to technical design discussions, code reviews, and documentation while continuing to strengthen engineering best practices Grow influence by improving data engineering standards, solution patterns, and data quality practices across projects and teams, building the depth of technical expertise and ownership expected for progression into a Senior Data Engineer role ML/AI Jump Path — For individuals interested in accelerating towards advanced analytics, AI, and ML‑driven leadership roles Support the development of AI/ML‑enabled data engineering solutions, including intelligent data quality, automated observability, and data workflows that enable AI‑driven use cases Work closely with the Decision Intelligence Group and other partners to support advanced analytics, ML, and AI use cases through reliable, well‑structured data Gain exposure and experience that prepares them for future technical growth within advanced analytics, AI/ML, or data engineering specialization roles Technical Managerial Path — For individuals motivated by people leadership and team development in a technical environment Build leadership skills through mentoring peers, sharing knowledge, and helping coordinate work across projects and team efforts Take on increasing responsibility in project delivery, stakeholder collaboration, and cross‑functional coordination across IT and business teams Experiences/Education – Required Bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related technical discipline 2+ years of experience in data engineering or related roles, with experience building, maintaining, and supporting ETL/ELT pipelines, data integration workflows, data warehouses, or cloud‑based data platforms Experience working with manufacturing, operational, or industrial data, including integrating and transforming data that supports production, quality, equipment, or supply chain processes 2+ years of programming experience in Python, with the ability to write clean, maintainable, and testable code Experience supporting data solutions used for analytics, reporting, or AI/ML applications, including exposure to AI‑enabled workflows, machine learning data preparation, or data pipelines that support intelligent automation Hands‑on experience with data processing and integration technologies such as Apache Spark, SQL‑based transformation tools, Kafka, or similar batch and streaming technologies Experience with cloud platforms such as AWS, GCP, or Azure, including familiarity with data storage, compute, and managed data services used in modern data architectures Proficiency in SQL, data modeling, and database technologies, including relational databases and modern data warehousing environments Strong communication and collaboration skills, with the ability to work effectively across cross‑functional teams including manufacturing, analytics, IT, and business stakeholders Experiences/Education – Desired Experience in manufacturing, industrial IoT, or scientific research environments, with exposure to time‑series data, sensor data ingestion, and high‑volume data processing from operational technology (OT) systems Proficiency or hands‑on experience with the following tools: Databases & Data Warehousing: Oracle, Microsoft SQL Server, PostreSQL Enterprise ETL & Integration Platforms: Informatica, Mulesoft, SSIS Open Source Data Integration & DAG Orchestration: Airflow, Dagster, Prefect Manufacturing & Industrial Data Sources: Pi Integrator, Camstar, Maximo Benefits Company‑wide bonuses and long‑term incentives align with key business results and ensure you are rewarded when the company performs well. When Corning wins, we all win. As part of our commitment to your financial well‑being and in addition to full Mexico statutory benefits, we offer food coupons that ease daily costs, and a structured savings fund to support your long‑term financial goals. Salaried employees are eligible for comprehensive medical and dental coverage. Additionally, all employees are covered by company‑sponsored life insurance, total permanent disability protection, paid time off, and have access to our Employee Assistance Program to support you and your family. Getting paid for our work is important, but feeling appreciated and recognized for those contributions motivates us much more. That’s why Corning offers a recognition program to celebrate successes and reward colleagues who make exceptional contributions. Corning is committed to providing equal employment opportunities and considers requests for reasonable accommodations in accordance with applicable laws. Individuals with disabilities or sincerely held religious beliefs may request reasonable accommodations to participate in the application or interview process, perform essential job functions, or access other benefits and privileges of employment. To submit a request for reasonable accommodation related to disability or religion, please contact us at . #J-18808-Ljbffr