Data Engineer

Requisition Number: 64424

 

Corning is vital to progress – in the industries we help shape and in the world we share.

 

We invent life-changing technologies using materials science. Our scientific and manufacturing expertise, boundless curiosity, and commitment to purposeful invention place us at the center of the way the world interacts, works, learns, and lives.

 

Our sustained investment in research, development, and invention means we’re always ready to solve the toughest challenges alongside our customers. 

 

The global Information Technology (IT) Function is leading efforts to align IT and Business Strategy, leverage IT investments, and optimize end to end business processes and associated information integration technologies.  Through these efforts, IT helps to improve the competitive position of Corning's businesses through IT enabled processes.  IT also delivers Information Technology applications, infrastructure, and project services in a cost efficient manner to Corning worldwide.

 

Data, automation and advanced analytics technologies are drastically transforming industrial manufacturers beyond point process automation to systemic, highly contextualized and data driven systems. Corning is building the foundational digital infrastructure for these company-wide efforts, and are looking for passionate, hard-working, and talented staff-level software engineers that will develop and enhance the data ingestion pipelines that are crucial to these efforts.

 

Overview

The Data Engineer, Advanced Analytics platforms will work with our core platform development team as well as domain experts, application developers, controls engineers and data scientists. Their primary responsibility will be to develop reliable and instrumented data ingestion pipelines that land inbound data from multiple process and operational data stores throughout the company to on-premise and cloud-based data lakes. These pipelines will require data validation and data profiling automation along with version control and CI/CD to ensure ongoing resiliency and maintainability of the inbound data flows supporting our advanced analytics projects.

 

Responsibilities

As a data engineer for our advanced analytics platforms, your main responsibilities will be:

• Design, test, deploy and maintain production big-data ingestion pipelines using established frameworks, patterns of practice, agile software development and CI/CD practices, working closely with the Principal Software Engineer – Data Ingestion
• Work with cross-organizational data source teams to define data ingestion requirements for structured, unstructured and semi-structured data, pilot their implementation, ensure the data source teams accept the resulting landed data as valid
• Define and implement automated validation and profiling capabilities needed to ensure reliable data delivery, using agile software development and CI/CD practices
• Work with data source teams, domain experts and data scientists to define data cleansing and data enrichment requirements for landed data
• Implement data cleansing and enrichment code using established patterns of practice
• Work with data source teams, domain experts and data scientists to validate landed, cleansed and enriched data, using agile software development and CI/CD practices, while ensuring that the final datasets are directly usable by them without additional processing effort
• Actively participate in code reviews and technical information sharing with your team members and the broader software engineering community at Corning
• Stay up to date with industry standards and technological advancements that will improve the quality, productivity and performance of your work.
• Provide support in a DevOps environment to monitor tokens, jobs and overall system performance.

 

Qualifications

• Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
• Understand concepts of big data engineering, developing and maintaining ETL and ELT pipelines for data warehousing, on-premise and cloud data lake environments
• Demonstrated production programm