Principal Architect, Data Product Delivery; Hybrid

Work Flexibility:
Hybrid

As a Principal Architect, Data Product Delivery, you will lead the design of scalable, secure, and maintainable data and analytics solutions across multiple programs and business domains. You will partner with Engineering, Product Management, Data Governance, Security, platform teams, and business stakeholders to translate strategy into practical architecture, delivery roadmaps, and reusable implementation patterns.

• Define architecture direction, standards, reference patterns, and reusable components for data ingestion, storage, transformation, analytics, and consumption.
• Own architecture diagrams, technical designs, integration blueprints, data models, standards, and architecture decision records for the Data and Analytics vertical.
• Develop proofs of concept, reference implementations, and reusable patterns that accelerate delivery and reduce technical debt.
• Evaluate emerging technologies, platforms, frameworks, and advanced analytics capabilities, and recommend fit-for-purpose adoption.
• Conduct architecture, design, and code reviews to assess scalability, performance, security, reliability, supportability, and engineering quality.
• Embed data privacy, access control, governance, and compliance requirements into solution designs with Data Governance and Security teams.
• Resolve complex performance, quality, scalability, integration, reliability, and operational challenges with engineering teams.
• Mentor engineers and architects through solution design, implementation planning, technical evaluations, and delivery reviews.
• Translate strategic requirements into technical designs, delivery roadmaps, and phased implementation plans with Product Management, platform teams, and business stakeholders.

• Apply enterprise data architecture practices across data warehousing, Lakehouse, real-time streaming, data engineering, integration, analytics, and operational support.
• Balance scalability, performance, cost, maintainability, delivery constraints, and engineering trade-offs when designing solutions.
• Analyze ambiguous, cross-functional technical challenges and explain architecture decisions and trade-offs to technical and executive audiences.
• Influence technical decisions through expertise, collaboration, and hands‑on leadership while staying current with relevant data and analytics technologies.

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related discipline.
• Minimum 8 years of experience in data engineering, solution architecture, or technical design roles, including architecture ownership.
• Experience architecting large-scale enterprise data platforms and integration solutions.
• Hands‑on experience with cloud data platforms, data modeling, modern data architecture patterns, Databricks or an equivalent Lakehouse platform, and guiding implementation teams through complex technical challenges.

• Master's degree in Computer Science, Information Systems, Engineering, or a related discipline.
• Experience with Azure Data Services, Databricks Lakehouse, Delta Lake, Delta Live Tables, Unity Catalog, SQL, Python, ETL/ELT, change data capture, dimensional modeling, medallion architecture, and distributed data processing.
• Experience with ERP and integration ecosystems such as Oracle, JDE, Salesforce, SAP S/4
  
  HANA, Kafka, REST, or GraphQL, including commercial, manufacturing, supply chain, or finance data domains.
• Cloud architecture certification such as AWS Solutions Architect, Azure Solutions Architect Expert, or GCP Professional Cloud Architect; TOGAF or an equivalent enterprise architecture certification.

• USN:…