Reynosa, TAM, MX, 88730
Open 4 months, first seen by us 126 days agoDesign, build, optimize and maintain batch and near-real-time ETL/ELT pipelines
Develop production-ready datasets for manufacturing visibility, analytics and AI/ML
Implement automated data-quality checks, monitoring and validation
Lead delivery of complex data engineering projects from design through deployment
Mentor data engineers through code reviews and technical guidance
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
Lead the technical delivery of complex Data Engineering projects, including solution design, development, testing, deployment, troubleshooting, and continuous improvement.
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.
Open 4 monthsWe first saw this posting 126 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
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Day 126
Up longer than most. Similar jobs usually come down between day 6 and day 56.
Well past Corning’s usual: its jobs come down by about day 42.
From 13,630 similar postings that came down, and 85 of Corning’s. Coming down is not always a hire.
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- 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, PySpark, SparkSQL, or comparable distributed data-processing technologies.
- Strong hands-on experience with Apache Spark, PySpark, SparkSQL, or comparable distributed data-processing technologies. - Advanced SQL skills and experience with data modeling, relational databases, data warehouses, data lakes, or lakehouse environments. - Experience working with manufacturing, production, industrial, operational, equipment, quality, or supply-chain data.
What would be helpful? - Experience with Databricks, Snowflake, Delta Lake, Parquet, Iceberg, PostgreSQL, MySQL, or Microsoft SQL Server.- Experience with Kafka, Flink, or other real-time and streaming technologies.- Experience with Airflow, Dagster, Prefect, or another data orchestration platform.- Exposure to AI/ML data pipelines, Large Language Models, AI agents, intelligent automation, or AI-enabled data-quality solutions.- Experience with time-series data, sensor data, industrial IoT, or operational technology systems.- Familiarity with PI Integrator, Camstar, Maximo, LangChain, LlamaIndex, or Semantic Kernel. What do we offer?
- Experience working with manufacturing, production, industrial, operational, equipment, quality, or supply-chain data. - Experience with cloud-based data platforms using AWS, Azure, or Google Cloud. AWS experience is strongly preferred. - Experience leading technical projects or independently owning complex Data Engineering initiatives.- Strong communication and collaboration skills, with the ability to explain technical solutions and architecture decisions to technical and non-technical stakeholders.
- 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, PySpark, SparkSQL, or comparable distributed data-processing technologies. - Advanced SQL skills and experience with data modeling, relational databases, data warehouses, data lakes, or lakehouse environments.
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New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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 global 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.
You will independently lead complex Data Engineering initiatives, collaborate with technical and business stakeholders, and provide guidance to other engineers through mentoring, code reviews, and knowledge sharing.Major responsibilities and tasks of the position:
- 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, PySpark, SparkSQL, or comparable distributed data-processing technologies.
- Advanced SQL skills and experience with data modeling, relational databases, data warehouses, data lakes, or lakehouse environments.
- Experience working with manufacturing, production, industrial, operational, equipment, quality, or supply-chain data.
- Experience with cloud-based data platforms using AWS, Azure, or Google Cloud. AWS experience is strongly preferred.
- Experience leading technical projects or independently owning complex Data Engineering initiatives.- Strong communication and collaboration skills, with the ability to explain technical solutions and architecture decisions to technical and non-technical stakeholders.
What would be helpful?
- Experience with Databricks, Snowflake, Delta Lake, Parquet, Iceberg, PostgreSQL, MySQL, or Microsoft SQL Server.- Experience with Kafka, Flink, or other real-time and streaming technologies.- Experience with Airflow, Dagster, Prefect, or another data orchestration platform.- Exposure to AI/ML data pipelines, Large Language Models, AI agents, intelligent automation, or AI-enabled data-quality solutions.- Experience with time-series data, sensor data, industrial IoT, or operational technology systems.- Familiarity with PI Integrator, Camstar, Maximo, LangChain, LlamaIndex, or Semantic Kernel.
What do we offer?
- A hybrid role based in Monterrey or Reynosa, Mexico.- The opportunity to lead technically challenging Data Engineering projects with direct impact on manufacturing and business operations.- Exposure to modern cloud platforms, distributed data processing, AI/ML-enabled solutions, and intelligent data-quality technologies.- Career-growth opportunities in Data Engineering subject-matter expertise, AI/ML specialization, technical leadership, or future people management.- Opportunities to mentor other engineers and influence Data Engineering standards and best practices.- Collaboration with global manufacturing, technology, analytics, and business teams.- Competitive compensation and benefits.
More about usCorning is one of the world’s leading innovators in glass, ceramic, and materials science. Our technologies help connect the world, advance communications, transform industries, and support products that improve everyday life.
Our Optical Communications business provides industry-leading fiber, cable, connectivity, and optical-network solutions used by businesses, governments, service providers, and individuals around the world.
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 accommodation 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 accommodations related to disability or religion, please contact us at accommodations@corning.com.
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Reynosa, TAM, MX, 88730
What do we offer? - A hybrid role based in Monterrey or Reynosa, Mexico.- The opportunity to lead technically challenging Data Engineering projects with direct impact on manufacturing and business operations.- Exposure to modern cloud platforms, distributed data processing, AI/ML-enabled solutions, and intelligent data-quality technologies.- Career-growth opportunities in Data Engineering subject-matter expertise, AI/ML specialization, technical leadership, or future people management.- Opportunities to mentor other engineers and influence Data Engineering standards and best practices.- Collaboration with global manufacturing, technology, analytics, and business teams.- Competitive compensation and benefits. More about usCorning is one of the world’s leading innovators in glass, ceramic, and materials science. Our technologies help connect the world, advance communications, transform industries, and support products that improve everyday life.
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