Senior Manager, Data & AI Architect; Remote

At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world.

Pratt & Whitney is a world leader in the design, manufacture and service of aircraft engines and auxiliary power systems and has been revolutionizing modern flight for over 100 years. Join us and help shape the future of aerospace and defense.

We are seeking an experienced Data & AI Architect to design, develop, and govern scalable, secure, and high-performing data architectures that support business intelligence, analytics, artificial intelligence, and operational needs. The Data Architect will work closely with business stakeholders, data engineers, application teams, security teams, and leadership to establish data strategies, standards, models, and platforms that enable reliable and accessible data across the organization.

The ideal candidate has hands‑on experience designing Databricks-based Lakehouse architectures, a strong understanding of the Medallion Architecture, including Bronze, Silver, and Gold data layers and experience architecting data solutions for SAP ECC to SAP S/4

HANA migrations.

• Design and implement scalable enterprise data architectures using Databricks and modern Lakehouse technologies.
• Define and implement Medallion Architecture patterns, including Bronze Layer, Silver Layer and Gold Layer.
• Architect and implement semantic layers that enable consistent enterprise metrics, business definitions, and analytics across heterogeneous systems.
• Design data models that blend ECC and S/4
  
  HANA structures into unified, analytics‑ready data products.
• Partner with SAP functional experts, data engineers, and business stakeholders to define data requirements, lineage, and transformation logic.
• Develop conceptual, logical, and physical data models aligned with business and technical requirements.
• Design scalable data lake, Lakehouse, and data warehouse architectures.
• Establish data architecture standards, principles, patterns, and best practices.
• Ensure alignment with enterprise governance, VAULTIS principles, and data quality standards.
• Design data ingestion and integration strategies for batch and streaming workloads.
• Partner with data engineers to develop efficient ETL/ELT pipelines using Databricks, Apache Spark, and SQL.
• Define approaches for data quality, lineage, metadata management, governance, and observability across the data platform.
• Design architectures that support analytics, business intelligence, machine learning, and generative AI use cases.
• Develop data migration and modernization strategies for legacy platforms.
• Ensure data architectures meet security, privacy, compliance, scalability, availability, and performance requirements.
• Collaborate with enterprise architects, application teams, data engineers, analysts, data scientists, and business stakeholders.
• Create architecture documentation, data-flow diagrams, reference architectures, and technical standards.
• Identify opportunities to improve data platform performance, reliability, scalability, and cost efficiency.
• Provide technical leadership and mentorship to data engineering and analytics teams.
• Collaborate with AI/ML teams to prepare, model, and structure SAP data for intelligent applications, including feature engineering and model‑ready datasets.

• Bachelor's degree in Computer Science,…