Principal Architect, Data & Analytics

Overview

Provide technical leadership for complex data and analytics solutions across multiple programs and business domains, translating business strategy into scalable, secure, and maintainable technology solutions.

What you'll do

• Define solution architecture direction, standards, and reference patterns for complex data and analytics initiatives, aligned with enterprise architecture principles.
• Own solution design artifacts including architecture diagrams, technical design documents, integration blueprints and data modeling.
• Define reference architectures, design patterns, and reusable components for data ingestion, storage, transformation, and consumption.
• Develop proof-of-concepts, reference implementations, and reusable implementation patterns that accelerate delivery and reduce technical debt.
• Evaluate emerging technologies, tools, and platforms, and recommend fit-for-purpose adoption.
• Conduct architecture, design and code reviews, and technical quality assessments for scalability, performance, security, reliability, and supportability.
• Partner with Data Governance and Security teams to embed data privacy, access control, and compliance requirements into solution designs.
• Lead proof-of-concepts and technical evaluations for new platforms, frameworks, advanced analytics capabilities, and architectural approaches.
• Partner with engineering teams to resolve complex performance, quality, scalability, reliability, integration, and operational challenges.
• Provide technical mentorship to engineers and architects through active engagement in solution design, implementation planning, and delivery reviews.
• Create, maintain and represent architecture documentation, standards, and decision records for the Data and Analytics vertical.
• Partner with Product Management, platform teams and business stakeholders to translate strategic requirements into technical designs, delivery roadmaps, and phased implementation plans.

What you'll need

• Deep expertise in enterprise data architecture, including data warehousing, Lakehouse, and real-time streaming architecture.
• Strong understanding of cloud platforms, modern data platform ecosystems, and implementation practices across data engineering, integration, analytics, and operational support.
• Ability to design solutions that balance scalability, performance, cost, and maintainability.
• Ability to balance strategic architecture considerations with practical implementation requirements, delivery constraints, and engineering trade-offs.
• Strong analytical and problem-solving skills applied to ambiguous, cross-functional technical challenges.
• Effectively communicates architectural decisions and trade-offs to technical and executive audiences.
• Builds credibility and influence across engineering, product, and governance teams without direct authority.
• Proven capability to influence technical decisions through expertise, collaboration, and hands-on technical leadership rather than formal authority.
• Stays current with industry trends and emerging technologies relevant to data and analytics architecture.
• 10+ years of experience in data engineering, solution architecture, or technical design roles, including significant architecture ownership.
• Demonstrated experience architecting large-scale, enterprise data platforms and integration solutions.
• Strong hands-on background in cloud data platforms, data modeling, modern data architecture patterns, Databricks or equivalent Lakehouse platforms, and engineering practices, with ability to guide implementation teams through complex technical challenges.
• Proven ability to influence technical direction across multiple teams without direct management authority.
• Excellent written and verbal communication skills, including experience presenting to senior stakeholders.

Nice to have

• Experience with modern cloud data platforms and Lakehouse technologies, including Azure Data Services, Databricks Lakehouse, Delta Lake, Delta Live Tables, Unity Catalog, or equivalent enterprise analytics platforms.
• Strong proficiency in SQL, Python, and modern data engineering concepts, including ETL/ELT, CDC, dimensional modeling, star-schema design, medallion architecture, distributed data processing, and workload performance optimization.
• Experience with enterprise integration patterns and ERP ecosystems such as Oracle, JDE, SFDC, SAP S/4HANA, including commercial, manufacturing, supply chain, and finance data domains (modern as well as legacy).
• Experience designing governed data products across bronze, silver, and gold layers, with clear lineage, data quality controls, reconciliation expectations, and consumption-ready semantic layers.
• Experience designing scalable analytics, reporting, semantic model, and business intelligence architectures, including Power BI semantic models, DAX, row-level security, refresh patterns, and performance optimization.
• Strong knowledge of API-based and event-driven integration architectures (Kafka, REST, GraphQL).
• Experience with infrastructure-as-code, CI/CD, observability, performance optimization, and DevOps practices in cloud-native data platforms.
• Familiarity with data governance, metadata management, and master data management (MDM) frameworks.
• Experience presenting architecture recommendations, solution trade-offs, and implementation approaches to senior technical and business stakeholders.

Details

• Work flexibility: Hybrid.
• Travel: approximately 10%.