• Design, develop, and maintain data pipelines using Azure Data Factory. • Develop data processing solutions with Azure Databricks, PySpark, and Spark SQL. • Structure and manage Data Lakes in Azure Blob Storage, applying layered architecture (raw, curated, trusted). • Model, optimize, and administer data in Azure SQL Database. • Develop and maintain analytical data models for consumption in Power BI. • Create and optimize datasets, semantic models, and DAX measures in Power BI. • Implement code versioning and CI/CD practices for pipelines and analytical artifacts. • Ensure data quality, reliability, and traceability (data quality, data lineage, and monitoring). • Collaborate with business, BI, and analytics teams to gather and translate technical requirements. • Support data architecture decisions, cost optimization (FinOps), and best practices in Azure. • Provide technical guidance to junior professionals.

• Share ownership and evolve the end-to-end data architecture across streaming, batch, and analytical workloads • Design data models that preserve signal from unstructured and semi-structured sources • Enable machine learning workflows by defining clear contracts between raw, derived, and model-ready data • Establish standards for schema evolution, dataset versioning, reproducibility, and data quality • Partner closely with engineering teams to improve scalability, reliability, and cost efficiency • Embed applied data science considerations into architectural decisions, including feature reuse, temporal consistency, and leakage prevention • Document and communicate architectural decisions clearly across teams**

• Define and evolve enterprise data architecture principles, standards, and reference architectures aligned to business priorities and modern practices • Lead the design and maintenance of enterprise conceptual, logical, and physical data structures, ensuring consistent definitions and shared semantics • Establish domain-oriented architecture patterns for reusable, governed data products and interoperable data flows • Develop architecture patterns supporting both batch and streaming workloads, including event-driven approaches and canonical representations • Partner with data engineering teams to translate architecture and logical designs into scalable physical implementations on AWS cloud data platforms • Ensure consistent data definitions, lineage, and metadata documentation across domains by enabling cataloging and lineage platforms • Maintain a central repository of architecture artifacts, definitions, and metadata documentation • Influence data design decisions across programs and projects through architecture reviews and standards enforcement • Facilitate architecture and data design workshops with business and technical stakeholders • Lead, mentor, and develop a team of data architects and specialists, ensuring consistent delivery of architecture outcomes • Stay current on evolving architecture trends and evaluate their applicability to Deckers

• Partner with the Director, Data Architecture to implement enterprise data architecture standards and ensure consistent adoption across domains and initiatives • Lead architecture design for assigned domains and initiatives, including conceptual, logical, and physical data structures aligned to business requirements and data products • Define and maintain domain-aligned data definitions and semantic consistency to support a unified understanding of key business entities and metrics • Develop architecture patterns that support batch and streaming use cases, including event-driven data flows and canonical representations • Collaborate with data engineering teams to translate architecture designs into scalable physical implementations on AWS cloud data platforms • Participate in architecture and design reviews, providing guidance, feedback, and enforcement of standards for new data products and platform changes • Partner with governance teams to align architecture with data quality, privacy, security, access controls, classification, retention, and metadata requirements • Maintain architecture artifacts and documentation in a central repository, including definitions, reference designs, and decision records to improve reuse and consistency • Facilitate workshops with business and technical stakeholders to capture requirements, refine definitions, and align on domain boundaries and ownership • Identify architecture gaps and improvement opportunities, and recommend practical enhancements to standards, patterns, and tooling that improve scalability and interoperability • Coach and enable engineers and analysts on architecture expectations and best practices through working sessions, office hours, and documentation