Remote Senior Architect - Data & AI/ML Platforms

Pratt & Whitney

United States

Remote

USD 132,000 - 252,000

Full time

14 days+

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Job summary

Pratt & Whitney is seeking a Senior Manager, Solutions Architect for Data, Analytics & AI/ML Platforms to define end-to-end data platform architecture and drive enterprise analytics modernization. You will guide Databricks, Azure, AWS, SAP integrations, and knowledge graphs across multiple domains while mentoring teams and aligning with business priorities.

The role requires deep technical leadership, strong stakeholder engagement, and the ability to deliver scalable, secure data solutions.

Qualifications

Bachelor's degree in Computer Science, Engineering, Data Science, or a related field with 10+ years of applicable work experience; OR an Advanced Degree with 7+ years of applicable work experience.
7+ years of experience in data engineering, data architecture, analytics, AI/ML, or related technical domains.
5+ years architecting cloud-native data platforms (Azure, AWS, or GCP). Deep experience with Databricks, Lakehouse architectures, and modern ELT/ETL tooling.
Strong understanding of distributed systems, real‑time data streaming, data governance, and API/Integration architectures.
Demonstrated ability to design and implement enterprise‑scale data architecture solutions.
Strong stakeholder management, communication, and executive engagement skills.

Responsibilities

Define the long‑term architecture for data, analytics, and AI/ML platforms in alignment with enterprise digital strategy.
Develop reference architectures, design patterns, and platform standards for cloud, Lakehouse, and AI ecosystems.
Define and lead technology proof of concepts to ensure feasibility of architecture solutions.
Provide strong thought leadership in pursuit of modern architecture principles and technology modernization.
Evaluate emerging technologies and provide strategic recommendations (AI, knowledge graphs, real‑time streaming, ML Ops, etc.).
Drive continuous technology transformation to minimize technical debt.
Architect end‑to‑end solutions spanning ingestion, transformation, governance, analytics, and ML operationalization.
Lead architectural design for platforms such as Databricks, Snowflake, Azure Data Services, SAP S/4 connectors, and enterprise knowledge graph/ontology platforms.
Define patterns for real‑time streaming, data virtualization, metadata frameworks, and multi‑cloud integration.
Ensure platform scalability, performance, redundancy, cost optimization, and security.
Collaborate with Cybersecurity and Data Governance teams to enforce data privacy, lineage, cataloging, and access control standards.
Ensure compliance with government regulations, export control, and enterprise security policies.
Provide architectural leadership across cross‑functional engineering teams and strategic programs.
Serve as a trusted advisor to business executives, product owners, and technical stakeholders.
Mentor and guide data engineers, architects, and analytics practitioners across the organization.
Lead architecture governance forums and design reviews for major programs.