**Date**:Oct 29, 2025
**Location**: Apodaca, NLE, MX, 66614
**Company**:Corning
Requisition Number: 71565
**The company built on breakthroughs.**
**Join us.**
Corning is one of the world’s leading innovators in glass, ceramic, and materials science. From the depths of the ocean to the farthest reaches of space, our technologies push the boundaries of what’s possible.
How do we do this? With our people. They break through limitations and expectations - not once in a career, but every day. They help move our company, and the world, forward.
At Corning, there are endless possibilities for making an impact. You can help connect the unconnected, drive the future of automobiles, transform at-home entertainment, and ensure the delivery of lifesaving medicines. And so much more.
Come break through with us.
Our Optical Communications segment has recently evolved from being a manufacturer of optical fiber and cable, hardware and equipment to being a comprehensive provider of industry-leading optical solutions across the broader communications industry.This segment is classified into two main product groupings - carrier network and enterprise network. The carrier network product group consists primarily of products and solutions for optical-based communications infrastructure for services such as video, data and voice communications. The enterprise network product group consists primarily of optical-based communication networks sold to businesses, governments and individuals for their own use.
**Purpose of Position.**
The Senior Data Analytics Engineer is responsible for architecting, developing, and optimizing advanced data platforms and analytical solutions that enable enterprise-level insights and data-driven decision-making. This role integrates big data engineering, advanced analytics, and automation to ensure data accuracy, scalability, and accessibility across the organization. The position plays a key role in guiding data strategy, driving innovation, and mentoring junior engineers and analysts.
**Mention the major responsibilities and tasks of the position.**
- Design and implement end-to-end data architectures supporting advanced analytics, AI/ML models, and large-scale data processing.
- Build, optimize, and maintain ETL/ELT pipelines in Databricks, leveraging distributed computing and Delta Lake technologies.
- Develop predictive and prescriptive models through statistical, machine learning, and data mining techniques.
- Ensure data integrity, governance, and lineage across complex data ecosystems.
- Collaborate with cross-functional teams to translate business challenges into analytical and technical solutions.
- Lead data strategy initiatives, ensuring consistency, scalability, and reusability across business units.
- Implement automation and orchestration for data workflows using tools such as Airflow, Azure Data Factory, or similar.
- Develop dashboards, reports, and visual analytics for leadership using Power BI, Tableau, or similar BI tools.
- Monitor data infrastructure performance and optimize for cost, latency, and reliability.
- Mentor junior team members and contribute to data best practices and standards.
- Stay at the forefront of emerging data technologies (AI/ML, streaming analytics, and cloud-native architectures).
**List the two most complex decisions indicative of this function and its impact to the function, department and/or corporation.**
1. Designing and implementing scalable big data architectures that balance performance, governance, and business agility, directly impacting enterprise data reliability and decision-making speed.
2. Defining analytical approaches and model frameworks that determine the accuracy and predictive power of insights used in strategic and operational decisions across the organization.
**Minimum Knowledge and Skill Requirements.**
- **Education**.**
- Bachelor’s degree in Engineering, Data Science, Mathematics, Statistics, or a related field.
- Master in Artificial Intelligence, Statistics or related.
**B. Work Experience.**:
- 5-8 years of experience in data engineering, data analytics, or related advanced analytics roles.
**C.** **Additional Skills.**:
- Expert knowledge of Databricks, and distributed computing frameworks.
- Strong proficiency in Python and SQL for data transformation and analytical modeling.
- Deep understanding of data architecture principles, data lakes, data warehouses, and ETL/ELT processes.
- Proven experience with big data ecosystems (Azure, AWS, or GCP) and tools like Azure Synapse, Snowflake, or Redshift.
- Strong background in statistics, predictive modeling, and machine learning algorithms.
- Expertise in data visualization tools (Power BI, Tableau, Looker) and storytelling through data.
- Familiarity with CI/CD pipelines, Git, and DevOps principles for data.
- Excellent communication and stakeholder management skills to translate complex data concepts into business insights.
- English proficiency (spoken and