IT Solutions Architect

Requisition Number: 76200

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.

Role Summary: The Data Architect is responsible for the design and evolution of our enterprise data architecture, with a strong focus on reusable data pipelines, data schemas & products, and modern data engineering practices. This role requires an AI-first mindset in data engineering and data modeling activities that enable the business to use data effectively and consistently across domains.

You will partner closely with product owners, data engineers, data analysts, and business stakeholders to:

• Define and maintain enterprise data models and domain boundaries using traditional and AI-enabled methods
• Design and govern reusable data assets and data products
• Establish standards and patterns for robust, scalable data pipelines
• Ensure data is discoverable, trustworthy, and fit-for-purpose for analytics, ML, and operational use cases

The ideal candidate blends deep technical expertise with strong business acumen and can translate complex business needs into clear, implementable data designs. They will evaluate and recommend different solutions and provide leadership to the product and engineering teams in delivering architecture, design, and development of solutions across multiple data products.

Essential Responsibilities:

Domain Data Architecture

• Define and evolve conceptual, logical, physical, canonical, and semantic data models across core business domains.
• Design reusable business entities, shared dimensions, reference data, metrics, and data structures that support enterprise-wide consistency and scalability.
• Partner with stakeholders to translate business processes, KPIs, and analytical needs into fit-for-purpose data models and semantic layers.

Data Products, Pipelines, and Platform Architecture

• Define standards for data products, including structure, naming, documentation, versioning, quality expectations, and lifecycle management.
• Design reusable ingestion, transformation, orchestration, and consumption patterns that scale across teams and use cases.
• Guide batch, near real-time, and event-driven pipeline architectures while partnering with engineering teams on reference architectures, templates, and production-ready assets.
• Ensure solutions are scalable, secure, reliable, cost-effective, observable, testable, and operationally sustainable.

Governance, Standards, and Technical Leadership

• Embed governance, security, compliance, lineage, metadata, retention, data quality, validation, cataloging, and access controls into architecture and design standards.
• Provide technical leadership and mentoring to drive consistent adoption of standards, patterns, and engineering best practices.
• Evaluate emerging technologies and architectural approaches and recommend solutions aligned to business priorities.

Qualifications/Requirements:

• 5-10 years of relevant IT experience, with at least 4+ years in a Data Architect, Senior Data Engineer, or similar role focused on data design and modeling.
• 5+ years of experience designing and implementing data models for analytics and operational reporting (dimensional, normalized, and/or domain-driven designs).
• 5+ years of experience building and/or guiding the development of ETL/ELT pipelines in cloud or modern data platforms.
• 4+ years of hands-on experience with Databricks or similar cloud-based lakehouse platforms supporting enterprise data lakes, data warehouses, and business intelligence
• 2+ years of experience using dbt (or similar transformation frameworks) including model structuring, tests, and documentation.
• Strong proficiency in SQL and experience with at least one programming language used in data engineering (Python or Scala preferred).
• Experience using Git and related DevOps tooling (GitHub/GitLab/Bitbucket, CI/CD pipelines such as GitHub Actions, Azure DevOps, Jenkins, etc.).
• Familiarity with modern data architecture paradigms such as data mesh and domain-oriented architecture

Desired Qualifications:

• Strong analytical problem-solving skills, with the ability to navigate ambiguity, make decisions with incomplete information, and drive consensus.
• Highly self-motivated, organized, and able to manage multiple priorities across technical and business stakeholders.
• Strong communication and presentation skills, including experience working effectively with distributed and/or international teams.
• Experience with data catalog, lineage, or metadata tools such as Collibra, Alation, Unity Catalog, or Purview is a plus.