Lead Data Engineer

Corning Incorporated; Monterrey; Presencial; MXN 900.000 - 1.400.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model in Monterrey or Reyn

Career-growth opportunities in Data“

Collaboration with global teams

Competitive compensation and benefits

Descripción de la vacante

Corning Incorporated in Monterrey, Mexico, seeks a Senior Data Engineer to design scalable data architectures and deliver robust ETL/ELT pipelines. You will lead technical direction, establish standards, and collaborate with manufacturing, analytics, IT, and business teams to align data solutions with strategic priorities.

You will operate in a hybrid role based in Monterrey or Reynosa, contributing to data-quality practices, platform strategy, and data products for analytics, AI/ML, and

Formación

• Must have a bachelor’s degree in a technical field.
• 5+ years of data engineering experience with pipelines, warehouses, lakes, or lakehouses.
• 5+ years of professional Python programming experience.
• Hands-on experience with Spark ecosystem (Spark, PySpark, SparkSQL).
• Experience with manufacturing or time-series data and data platforms on cloud.
• Demonstrated technical leadership and architectural influence.
• Advanced SQL and data modeling across modern data platforms.
• Cloud experience with AWS, Azure, or Google Cloud (AWS preferred).
• Strong communication skills for cross-team collaboration.

Responsabilidades

• Define and evolve scalable data architectures, platforms, pipelines, and curated data products for manufacturing analytics and AI/ML.
• Lead design, development, optimization, and delivery of ETL/ELT pipelines and distributed data-processing solutions.
• Establish data engineering standards, data-quality frameworks, observability, governance, and documentation.
• Provide technical leadership through architecture reviews, mentoring, and code reviews.
• Partner with manufacturing, analytics, IT, and business teams to align data solutions with strategy.

Conocimientos

Data engineering

Python

Apache Spark

PySpark

SparkSQL

Technical leadership

SQL

Data modeling

Cloud platforms

AWS

Azure

Google Cloud

Communication

Educación

Bachelor’s degree in Computer Science, Engineering, Statistics, Mathematics, or another related technical discipline

Herramientas

Databricks

Snowflake

Delta Lake

Parquet

Iceberg

PostgreSQL

MySQL

Oracle

Microsoft SQL Server

Kafka

Flink

Airflow

Dagster

Prefect

LangChain

Descripción del empleo

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 Google Cloud. AWS experience is strongly preferred.
• Strong communication skills, with the ability to explain technical strategies and architecture decisions to technical teams, business stakeholders, and senior leaders.

What would be helpful?

• Experience with Databricks, Snowflake, Delta Lake, Parquet, Iceberg, PostgreSQL, MySQL, Oracle, or Microsoft SQL Server.
• Experience with Kafka, Flink, or other streaming and near‑real‑time data technologies.
• Experience with Airflow, Dagster, Prefect, or another workflow‑orchestration platform.
• Exposure to AI/ML data pipelines, Large Language Models, AI agents, intelligent data observability, or AI‑enabled data‑quality solutions.
• Familiarity with LangChain, LlamaIndex, Semantic Kernel, or prompt‑engineering practices.
• Experience with industrial IoT, operational technology systems, PI Integrator, Camstar, or Maximo.
• Experience with infrastructure‑as‑code technologies such as Terraform or CloudFormation.
• Experience with Informatica, MuleSoft, SSIS, or other enterprise data‑integration tools.

What do we offer?

• A hybrid role based in Monterrey or Reynosa, Mexico.
• The opportunity to define technical direction while remaining hands‑on with Data Engineering delivery.
• Direct influence over data architecture, platform strategy, engineering standards, and data‑quality practices.
• Exposure to modern cloud platforms, distributed processing, manufacturing data, AI/ML, and intelligent automation.
• The opportunity to mentor Data Engineers and Senior Data Engineers and help build the next generation of technical leaders.
• Career‑growth opportunities in Data Engineering subject‑matter expertise, AI/ML specialization, enterprise architecture, or future technical management.
• Collaboration with global manufacturing, technology, analytics, and business teams.
• Competitive compensation and benefits.

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 [e-mail].