Senior Principal Architect, EDT Data Architecture Strategy & Standards

Overview

Senior Principal Architect owning the enterprise data and analytics architecture strategy, standards and design patterns for the global Azure/Databricks Lakehouse ecosystem, staying hands-on in design, prototyping and code review.

What you'll do

• Define and own the enterprise data and analytics reference architecture and multi-year roadmap across the Azure Lakehouse estate, including ADLS, Databricks, Delta Lake, Unity Catalog, Power BI, Databricks Genie and Copilot-based AI experiences.
• Build and maintain working reference implementations and reusable blueprints for lakehouse zoning, Delta table design, ingestion and orchestration, semantic models and Unity Catalog security patterns, validated through executable code, deployment scripts and representative data workloads.
• Co-chair the architecture review board with formal approval rights at defined design gates, review solution artifacts in detail, challenge design assumptions, and document Architecture Decision Records.
• Personally validate high-risk decisions through targeted prototypes or code reviews, and step into critical initiatives when architectural drift or technical blockers emerge.
• Personally design and build end-to-end batch and streaming solutions, including CDC ingestion, Auto Loader, Databricks Workflows/DLT, ADF orchestration and PySpark/SQL medallion transformations.
• Review production code and pipeline design at the pull-request level, reproduce performance issues, tune Spark jobs and compute configurations, assess DBU efficiency, and pair with engineers on improvements.
• Create and exercise engineering lifecycle standards for data quality, automated testing, CI/CD, observability, lineage and recovery, running PoCs, architecture spikes and hands-on solution health assessments before broad adoption.
• Serve as the senior technical counterpart to Microsoft and Databricks by testing preview capabilities in sandbox environments and converting vendor direction into practical reference patterns, guardrails and implementation recommendations.

What you'll need

• Bachelor's or master's degree from an accredited university in Computer Science, Engineering, Information Systems, Business, or equivalent field of study.
• 10+ years of progressive experience in data engineering, data architecture and analytics across large, global enterprises, including recent hands-on delivery on Azure/Databricks Lakehouse platforms.
• Demonstrated design and build depth: ability to walk through data platforms and pipelines personally architected and implemented, not solely governance, advisory or oversight experience.
• Expert-level command of Azure, ADLS, Databricks (Spark, Delta Lake, Unity Catalog, Workflows/DLT), modern data engineering practices and Power BI.
• Proven experience defining and operationalizing enterprise architecture standards, reference architectures, and design authority or architecture review processes.
• Track record of influencing and redirecting technical decisions across engineering teams through credibility and expertise, including intervening in in-flight designs and driving remediation.
• Strong grounding in data security, privacy and regulated-environment requirements (e.g., GxP, HIPAA, PII/PHI handling) and how they translate into architectural controls.
• Excellent communication skills, operating credibly in both executive forums and deep technical design sessions.

Nice to have

• Good knowledge of Databricks Genie and Microsoft Copilot.

Details

• Work mode: Hybrid or Onsite.
• Travel: None.